@conference {13362,
	title = {Declarative analysis of noisy information networks},
	booktitle = {2011 IEEE 27th International Conference on Data Engineering Workshops (ICDEW)},
	year = {2011},
	month = {2011/04/11/16},
	pages = {106 - 111},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {There is a growing interest in methods for analyzing data describing networks of all types, including information, biological, physical, and social networks. Typically the data describing these networks is observational, and thus noisy and incomplete; it is often at the wrong level of fidelity and abstraction for meaningful data analysis. This has resulted in a growing body of work on extracting, cleaning, and annotating network data. Unfortunately, much of this work is ad hoc and domain-specific. In this paper, we present the architecture of a data management system that enables efficient, declarative analysis of large-scale information networks. We identify a set of primitives to support the extraction and inference of a network from observational data, and describe a framework that enables a network analyst to easily implement and combine new extraction and analysis techniques, and efficiently apply them to large observation networks. The key insight behind our approach is to decouple, to the extent possible, (a) the operations that require traversing the graph structure (typically the computationally expensive step), from (b) the operations that do the modification and update of the extracted network. We present an analysis language based on Datalog, and show how to use it to cleanly achieve such decoupling. We briefly describe our prototype system that supports these abstractions. We include a preliminary performance evaluation of the system and show that our approach scales well and can efficiently handle a wide spectrum of data cleaning operations on network data.},
	keywords = {Cleaning, Data analysis, data cleaning operations, data management system, data mining, Databases, Datalog, declarative analysis, graph structure, information networks, Noise measurement, noisy information networks, Prediction algorithms, semantics, Syntactics},
	isbn = {978-1-4244-9195-7},
	doi = {10.1109/ICDEW.2011.5767619},
	author = {Moustafa,W. E and Namata,G. and Deshpande, Amol and Getoor, Lise}
}
@article {14485,
	title = {Eighth workshop on mining and learning with graphs},
	journal = {SIGKDD Explor. Newsl.},
	volume = {12},
	year = {2011},
	month = {2011/03//},
	pages = {63 - 65},
	abstract = {The Eighth Workshop on Mining and Learning with Graphs (MLG)1was held at KDD 2010 in Washington DC. It brought together a variete of researchers interested in analyzing data that is best represented as a graph. Examples include the WWW, social networks, biological networks, communication networks, and many others. The importance of being able to effectively mine and learn from such data is growing, as more and more structured and semi-structured data is becoming available. This is a problem across widely different fields such as economics, statistics, social science, physics and computer science, and is studied within a variety of sub-disciplines of machine learning and data mining including graph mining, graphical models, kernel theory, statistical relational learning, etc. The objective of this workshop was to bring together practitioners from these various fields and areas to foster a rich discussion of which problems we work on, how we frame them in the context of graphs, which tools and algorithms we apply and our general findings and lessons learned. This year{\textquoteright}s workshop was very successful with well over 100 attendees, excellent keynote speakers and papers. This is a rapidly growing area and we believe that this community is only in its infancy. We hope that the readers will join us next year for MLG 2011.},
	keywords = {data mining, dynamic network analysis, graph mining, kernel methods, link mining, machine learning, network analysis, pattern recognition, relational learning, scalable graph mining, statistical relational learning},
	isbn = {1931-0145},
	doi = {10.1145/1964897.1964915},
	url = {http://doi.acm.org/10.1145/1964897.1964915},
	author = {Brefeld,Ulf and Getoor, Lise and Macskassy,Sofus A.}
}
@conference {14471,
	title = {A probabilistic approach for learning folksonomies from structured data},
	booktitle = {Proceedings of the fourth ACM international conference on Web search and data mining},
	series = {WSDM {\textquoteright}11},
	year = {2011},
	month = {2011///},
	pages = {555 - 564},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Learning structured representations has emerged as an important problem in many domains, including document and Web data mining, bioinformatics, and image analysis. One approach to learning complex structures is to integrate many smaller, incomplete and noisy structure fragments. In this work, we present an unsupervised probabilistic approach that extends affinity propagation [7] to combine the small ontological fragments into a collection of integrated, consistent, and larger folksonomies. This is a challenging task because the method must aggregate similar structures while avoiding structural inconsistencies and handling noise. We validate the approach on a real-world social media dataset, comprised of shallow personal hierarchies specified by many individual users, collected from the photosharing website Flickr. Our empirical results show that our proposed approach is able to construct deeper and denser structures, compared to an approach using only the standard affinity propagation algorithm. Additionally, the approach yields better overall integration quality than a state-of-the-art approach based on incremental relational clustering.},
	keywords = {collective knowledge, data mining, folksonomies, social information processing, social metadata, taxonomies},
	isbn = {978-1-4503-0493-1},
	doi = {10.1145/1935826.1935905},
	url = {http://doi.acm.org/10.1145/1935826.1935905},
	author = {Plangprasopchok,Anon and Lerman,Kristina and Getoor, Lise}
}
@book {16975,
	title = {Analyzing Social Media Networks with NodeXL},
	year = {2010},
	month = {2010/08/27/},
	publisher = {Morgan Kaufmann},
	organization = {Morgan Kaufmann},
	abstract = {"Analyzing Social Media Networks with NodeXL provides a much needed resource for the social media research community, as it describes network theory, provides compelling examples using data sources like Twitter and Flickr, and highlights how to use a free sophisticated tool for analysis. This is the perfect book for anyone trying to analyze the behavior of online social networks and beyond." ---Adam Perer, Research Scientist, IBM Research  "This book provides a basic introduction to social network analysis, followed by practical instruction and examples on gathering data from online sources, importing into Excel, and then analyzing the data through Excel. The book will be important for promoting research in the area for those in information science, sociology, cultural studies, virtual community, and e-commerce."---Caroline Haythornthwaite, PhD, Professor, Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign  Businesses, entrepreneurs, individuals, and government agencies alike are looking to social network analysis (SNA) tools for insight into trends, connections, and fluctuations in social media. Microsoft{\textquoteright}s NodeXL is a free, open-source SNA plug-in for use with Excel. It provides instant graphical representation of relationships of complex networked data. But it goes further than other SNA tools - NodeXL was developed by a multidisciplinary team of experts that bring together information studies, computer science, sociology, human-computer interaction, and over 20 years of visual analytic theory and information visualization into a simple tool anyone can use. This makes NodeXL of interest not only to end-users but also to researchers and students studying visual and network analytics and their application in the real world.},
	keywords = {Business \& Economics / Marketing / Research, Computers / Computer Science, Computers / Data Processing, Computers / Database Management / Data Mining, Computers / General, Computers / Information Theory, Computers / Interactive \& Multimedia, Computers / Social Aspects / General, Computers / Social Aspects / Human-Computer Interaction, Computers / User Interfaces, data mining, Data mining - Computer programs, Data mining/ Computer programs, Information Visualization, Information visualization - Computer programs, Information visualization/ Computer programs, NodeXL, online social networks, Social Science / General, Social Science / Reference, Social Science / Sociology / General, Technology \& Engineering / General, Technology \& Engineering / Social Aspects, Webometrics, Webometrics - Computer programs, Webometrics/ Computer programs},
	isbn = {9780123822291},
	author = {Hansen,Derek and Shneiderman, Ben and Smith,Marc A.}
}
@conference {14449,
	title = {Constructing folksonomies by integrating structured metadata},
	booktitle = {Proceedings of the 19th international conference on World wide web},
	series = {WWW {\textquoteright}10},
	year = {2010},
	month = {2010///},
	pages = {1165 - 1166},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Aggregating many personal hierarchies into a common taxonomy, also known as a folksonomy, presents several challenges due to its sparseness, ambiguity, noise, and inconsistency. We describe an approach to folksonomy learning based on relational clustering that addresses these challenges by exploiting structured metadata contained in personal hierarchies. Our approach clusters similar hierarchies using their structure and tag statistics, then incrementally weaves them into a deeper, bushier tree. We study folksonomy learning using social metadata extracted from the photo-sharing site Flickr. We evaluate the learned folksonomy quantitatively by automatically comparing it to a reference taxonomy created by the Open Directory Project. Our empirical results suggest that the proposed approach improves upon the state-of-the-art folksonomy learning method.},
	keywords = {collective knowledge, data mining, folksonomies},
	isbn = {978-1-60558-799-8},
	doi = {10.1145/1772690.1772856},
	url = {http://doi.acm.org/10.1145/1772690.1772856},
	author = {Plangprasopchok,Anon and Lerman,Kristina and Getoor, Lise}
}
@conference {14446,
	title = {Growing a tree in the forest: constructing folksonomies by integrating structured metadata},
	booktitle = {Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining},
	series = {KDD {\textquoteright}10},
	year = {2010},
	month = {2010///},
	pages = {949 - 958},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {Many social Web sites allow users to annotate the content with descriptive metadata, such as tags, and more recently to organize content hierarchically. These types of structured metadata provide valuable evidence for learning how a community organizes knowledge. For instance, we can aggregate many personal hierarchies into a common taxonomy, also known as a folksonomy, that will aid users in visualizing and browsing social content, and also to help them in organizing their own content. However, learning from social metadata presents several challenges, since it is sparse, shallow, ambiguous, noisy, and inconsistent. We describe an approach to folksonomy learning based on relational clustering, which exploits structured metadata contained in personal hierarchies. Our approach clusters similar hierarchies using their structure and tag statistics, then incrementally weaves them into a deeper, bushier tree. We study folksonomy learning using social metadata extracted from the photo-sharing site Flickr, and demonstrate that the proposed approach addresses the challenges. Moreover, comparing to previous work, the approach produces larger, more accurate folksonomies, and in addition, scales better.},
	keywords = {collective knowledge, data mining, folksonomies, relational clustering, social information processing, social metadata, taxonomies},
	isbn = {978-1-4503-0055-1},
	doi = {10.1145/1835804.1835924},
	url = {http://doi.acm.org/10.1145/1835804.1835924},
	author = {Plangprasopchok,Anon and Lerman,Kristina and Getoor, Lise}
}
@conference {14316,
	title = {Mining Public Transport Usage for Personalised Intelligent Transport Systems},
	booktitle = {2010 IEEE 10th International Conference on Data Mining (ICDM)},
	year = {2010},
	month = {2010},
	pages = {887 - 892},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Traveller information, route planning, and service updates have become essential components of public transport systems: they help people navigate built environments by providing access to information regarding delays and service disruptions. However, one aspect that these systems lack is a way of tailoring the information they offer in order to provide personalised trip time estimates and relevant notifications to each traveller. Mining each user{\textquoteright}s travel history, collected by automated ticketing systems, has the potential to address this gap. In this work, we analyse one such dataset of travel history on the London underground. We then propose and evaluate methods to (a) predict personalised trip times for the system users and (b) rank stations based on future mobility patterns, in order to identify the subset of stations that are of greatest interest to the user and thus provide useful travel updates.},
	keywords = {automated ticketing systems, data mining, Intelligent Transport Systems, London underground, mobility patterns, personalised intelligent transport systems, personalised trip times, Personalization, public administration, public information systems, public transport systems, rapid transit systems, route planning, service disruptions, service updates, traffic information systems, travel history, traveller information},
	isbn = {978-1-4244-9131-5},
	doi = {10.1109/ICDM.2010.46},
	author = {Lathia,N. and Jon Froehlich and Capra,L.}
}
@conference {15918,
	title = {Sectored Random Projections for Cancelable Iris Biometrics},
	booktitle = {2010 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP)},
	year = {2010},
	month = {2010/03//},
	pages = {1838 - 1841},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Privacy and security are essential requirements in practical biometric systems. In order to prevent the theft of biometric patterns, it is desired to modify them through revocable and non invertible transformations called Cancelable Biometrics. In this paper, we propose an efficient algorithm for generating a Cancelable Iris Biometric based on Sectored Random Projections. Our algorithm can generate a new pattern if the existing one is stolen, retain the original recognition performance and prevent extraction of useful information from the transformed patterns. Our method also addresses some of the drawbacks of existing techniques and is robust to degradations due to eyelids and eyelashes.},
	keywords = {biometric pattern, Biometrics, Cancelable Biometrics, cancelable iris biometrics, data mining, data privacy, Degradation, Eyelashes, Eyelids, Iris, iris recognition, pattern recognition, privacy, random processes, Random Projections, Robustness, sectored random projection, Secure Biometrics, Security, security of data},
	isbn = {978-1-4244-4295-9},
	doi = {10.1109/ICASSP.2010.5495383},
	author = {Pillai,J.K. and Patel, Vishal M. and Chellapa, Rama and Ratha,N. K}
}
@conference {17423,
	title = {The state of visual analytics: Views on what visual analytics is and where it is going},
	booktitle = {2010 IEEE Symposium on Visual Analytics Science and Technology (VAST)},
	year = {2010},
	month = {2010/10/25/26},
	pages = {257 - 259},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In the 2005 publication "Illuminating the Path" visual analytics was defined as "the science of analytical reasoning facilitated by interactive visual interfaces." A lot of work has been done in visual analytics over the intervening five years. While visual analytics started in the United States with a focus on security, it is now a worldwide research agenda with a broad range of application domains. This is evidenced by efforts like the European VisMaster program and the upcoming Visual Analytics and Knowledge Discovery (VAKD) workshop, just to name two.There are still questions concerning where and how visual analytics fits in the large body of research and applications represented by the VisWeek community. This panel will present distinct viewpoints on what visual analytics is and its role in understanding complex information in a complex world. The goal of this panel is to engender discussion from the audience on the emergence and continued advancement of visual analytics and its role relative to fields of related research. Four distinguished panelists will provide their perspective on visual analytics focusing on what it is, what it should be, and thoughts about a development path between these two states. The purpose of the presentations is not to give a critical review of the literature but rather to give a review on the field and to provide a contextual perspective based on the panelists{\textquoteright} years of experience and accumulated knowledge.},
	keywords = {analytical reasoning, Data analysis, data mining, data visualisation, European VisMaster program, interactive visual interfaces, knowledge discovery, United States, visual analytics, VisWeek community},
	isbn = {978-1-4244-9488-0},
	doi = {10.1109/VAST.2010.5649078},
	author = {May,R. and Hanrahan,P. and Keim,D. A and Shneiderman, Ben and Card,S.}
}
@conference {13364,
	title = {Ef?cient Query Evaluation over Temporally Correlated Probabilistic Streams},
	booktitle = {IEEE 25th International Conference on Data Engineering, 2009. ICDE {\textquoteright}09},
	year = {2009},
	month = {2009/04/29/March},
	pages = {1315 - 1318},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In this paper, we address the problem of efficient query evaluation over highly correlated probabilistic streams. We observe that although probabilistic streams tend to be strongly correlated in space and time, the correlations are usually quite structured (i.e., the same set of dependencies and independences repeat across time) and Markovian (i.e., the state at time "t+1" is independent of the states at previous times given the state at time "t"). We exploit this observation to compactly encode probabilistic streams by decoupling the correlation structure (the set of dependencies) from the actual probability values. We develop novel stream processing operators that can efficiently and incrementally process new data items; our operators are based on the previously proposed framework of viewing probabilistic query evaluation as inference over probabilistic graphical models (PGMs) [P. Sen and A. Deshpande, 2007]. We develop a query planning algorithm that constructs efficient query plans that are executable in polynomial-time whenever possible, and we characterize queries for which such plans are not possible. Finally we conduct an extensive experimental evaluation that illustrates the advantages of exploiting the structured nature of correlations in probabilistic streams.},
	keywords = {Birds, Computerized monitoring, correlated probabilistic streams, correlation structure, Data engineering, data mining, Databases, Event detection, Graphical models, inference mechanisms, Markov processes, polynomial time, probabilistic database, probabilistic graphical model, probabilistic query evaluation, query evaluation, query planning algorithm, query plans, Query processing, Random variables, stream processing operator, Streaming media},
	isbn = {978-1-4244-3422-0},
	doi = {10.1109/ICDE.2009.229},
	author = {Kanagal,B. and Deshpande, Amol}
}
@conference {14451,
	title = {Identifying graphs from noisy and incomplete data},
	booktitle = {Proceedings of the 1st ACM SIGKDD Workshop on Knowledge Discovery from Uncertain Data},
	series = {U {\textquoteright}09},
	year = {2009},
	month = {2009///},
	pages = {23 - 29},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {There is a growing wealth of data describing networks of various types, including social networks, physical networks such as transportation or communication networks, and biological networks. At the same time, there is a growing interest in analyzing these networks, in order to uncover general laws that govern their structure and evolution, and patterns and predictive models to develop better policies and practices. However, a fundamental challenge in dealing with this newly available observational data describing networks is that the data is often of dubious quality -- it is noisy and incomplete -- and before any analysis method can be applied, the data must be cleaned, and missing information inferred. In this paper, we introduce the notion of graph identification, which explicitly models the inference of a "cleaned" output network from a noisy input graph. It is this output network that is appropriate for further analysis. We present an illustrative example and use the example to explore the types of inferences involved in graph identification, as well as the challenges and issues involved in combining those inferences. We then present a simple, general approach to combining the inferences in graph identification and experimentally show the utility of our combined approach and how the performance of graph identification is sensitive to the inter-dependencies among these inferences.},
	keywords = {classification, data mining, entity resolution, link prediction, social networks, statistical relational learning},
	isbn = {978-1-60558-675-5},
	doi = {10.1145/1610555.1610559},
	url = {http://doi.acm.org/10.1145/1610555.1610559},
	author = {Namata,Jr.,Galileo Mark S. and Getoor, Lise}
}
@article {17238,
	title = {Integrating Statistics and Visualization for Exploratory Power: From Long-Term Case Studies to Design Guidelines},
	journal = {IEEE Computer Graphics and Applications},
	volume = {29},
	year = {2009},
	month = {2009/06//May},
	pages = {39 - 51},
	abstract = {Evaluating visual-analytics systems is challenging because laboratory-based controlled experiments might not effectively represent analytical tasks. One such system, Social Action, integrates statistics and visualization in an interactive exploratory tool for social network analysis. This article describes results from long-term case studies with domain experts and extends established design goals for information visualization.},
	keywords = {case studies, Control systems, Data analysis, data mining, data visualisation, Data visualization, data-mining, design guidelines, Employment, exploration, Filters, Guidelines, Information Visualization, insights, laboratory-based controlled experiments, Performance analysis, social network analysis, Social network services, social networking (online), social networks, SocialAction, statistical analysis, Statistics, visual analytics, visual-analytics systems, Visualization},
	isbn = {0272-1716},
	doi = {10.1109/MCG.2009.44},
	author = {Perer,A. and Shneiderman, Ben}
}
@conference {15062,
	title = {A topic-based Document Correlation Model},
	booktitle = {Machine Learning and Cybernetics, 2008 International Conference on},
	volume = {5},
	year = {2008},
	month = {2008/07//},
	pages = {2487 - 2491},
	abstract = {Document correlation analysis is now a focus of study in text mining. This paper proposed a Document Correlation Model to capture the correlation between documents from topic level. The model represents the document correlation as the Optimal Matching of a bipartite graph, of which each partition is a document, each node is a topic, and each edge is the similarity between two topics. The topics of each document are retrieved by the Latent Dirichlet Allocation model and Gibbs sampling. Experiments on correlated document search show that the Document Correlation Model outperforms the Vector Space Model on two aspects: 1) it has higher average retrieval precision; 2) it needs less space to store a documentpsilas information.},
	keywords = {bipartite graph optimal matching, data mining, document correlation analysis, document retrieval, Gibbs sampling, Information retrieval, latent Dirichlet allocation model, text analysis, text mining, topic-based document correlation model},
	doi = {10.1109/ICMLC.2008.4620826},
	author = {Jia,Xi-Ping and Peng,Hong and Zheng,Qi-Lun and Zhuolin Jiang and Li,Zhao}
}
@conference {18919,
	title = {Reactive Query Policies: A Formalism for Planning with Volatile External Information},
	year = {2007},
	month = {2007/04/01/5},
	pages = {243 - 250},
	abstract = {To generate plans for collecting data for data mining, an important problem is information volatility during planning: the information needed by the planning system may change or expire during the planning process, as changes occur in the data being collected. In such situations, the planning system faces two challenges: how to generate plans despite these changes, and how to guarantee that a plan returned by the planner will remain valid for some period of time after the planning ends. The focus of our work is to address both of the above challenges. In particular, we provide: 1) A formalism for reactive query policies, a class of strategies for deciding when to reissue queries for information that has changed during the planning process. This class includes all query management strategies that have yet been developed. 2) A new reactive query policy called the presumptive strategy. In our experiments, the presumptive strategy ran exponentially faster than the lazy strategy, the best previously known query management strategy. In the hardest set of problems we tested, the presumptive strategy took 4.7\% as much time and generated 6.9\% as many queries as the lazy strategy},
	keywords = {data collection, data mining, information volatility, planning (artificial intelligence), planning system, presumptive strategy, query management, Query processing, reactive query policies, volatile external information},
	doi = {10.1109/CIDM.2007.368880},
	author = {Au,Tsz-Chiu and Nau, Dana S.}
}
@conference {13402,
	title = {Representing Tuple and Attribute Uncertainty in Probabilistic Databases},
	booktitle = {Seventh IEEE International Conference on Data Mining Workshops, 2007. ICDM Workshops 2007},
	year = {2007},
	month = {2007/10/28/31},
	pages = {507 - 512},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {There has been a recent surge in work in probabilistic databases, propelled in large part by the huge increase in noisy data sources-sensor data, experimental data, data from uncurated sources, and many others. There is a growing need to be able to flexibly represent the uncertainties in the data, and to efficiently query the data. Building on existing probabilistic database work, we present a unifying framework which allows a flexible representation of correlated tuple and attribute level uncertainties. An important capability of our representation is the ability to represent shared correlation structures in the data. We provide motivating examples to illustrate when such shared correlation structures are likely to exist. Representing shared correlations structures allows the use of sophisticated inference techniques based on lifted probabilistic inference that, in turn, allows us to achieve significant speedups while computing probabilities for results of user-submitted queries.},
	keywords = {attribute uncertainty, Computer science, Conferences, correlation structures, data mining, Data models, database management systems, Educational institutions, inference mechanisms, noisy data sources, probabilistic database, probabilistic inference, Probability distribution, Query processing, Relational databases, Sensor phenomena and characterization, tuple representation, Uncertainty, uncertainty handling},
	isbn = {978-0-7695-3019-2},
	doi = {10.1109/ICDMW.2007.11},
	author = {Sen,P. and Deshpande, Amol and Getoor, Lise}
}
@conference {13357,
	title = {Approximate Data Collection in Sensor Networks using Probabilistic Models},
	booktitle = {Proceedings of the 22nd International Conference on Data Engineering, 2006. ICDE {\textquoteright}06},
	year = {2006},
	month = {2006/04/03/07},
	pages = {48 - 48},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Wireless sensor networks are proving to be useful in a variety of settings. A core challenge in these networks is to minimize energy consumption. Prior database research has proposed to achieve this by pushing data-reducing operators like aggregation and selection down into the network. This approach has proven unpopular with early adopters of sensor network technology, who typically want to extract complete "dumps" of the sensor readings, i.e., to run "SELECT *" queries. Unfortunately, because these queries do no data reduction, they consume significant energy in current sensornet query processors. In this paper we attack the "SELECT " problem for sensor networks. We propose a robust approximate technique called Ken that uses replicated dynamic probabilistic models to minimize communication from sensor nodes to the network{\textquoteright}s PC base station. In addition to data collection, we show that Ken is well suited to anomaly- and event-detection applications. A key challenge in this work is to intelligently exploit spatial correlations across sensor nodes without imposing undue sensor-to-sensor communication burdens to maintain the models. Using traces from two real-world sensor network deployments, we demonstrate that relatively simple models can provide significant communication (and hence energy) savings without undue sacrifice in result quality or frequency. Choosing optimally among even our simple models is NPhard, but our experiments show that a greedy heuristic performs nearly as well as an exhaustive algorithm.},
	keywords = {Batteries, Biological system modeling, Biosensors, data mining, Databases, Energy consumption, Intelligent networks, Intelligent sensors, Robustness, Wireless sensor networks},
	isbn = {0-7695-2570-9},
	doi = {10.1109/ICDE.2006.21},
	author = {Chu,D. and Deshpande, Amol and Hellerstein,J. M and Wei Hong}
}
@conference {19493,
	title = {Eye of the Beholder: Phone-Based Text-Recognition for the Visually-Impaired},
	booktitle = {2006 10th IEEE International Symposium on Wearable Computers},
	year = {2006},
	month = {2006///},
	pages = {145 - 146},
	abstract = {Blind and visually-impaired people cannot access essential information in the form of written text in our environment (e.g., on restaurant menus, street signs, door labels, product names and instructions, expiration dates). In this paper, we present and evaluate a mobile text-recognition system capable of extracting written information from a wide variety of sources and communicating it on-demand to the user. The user needs no additional hardware except an ordinary, Internet- enabled mobile camera-phone - a device that many visually-impaired individuals already own. This approach fills a gap in assistive technologies for the visually- impaired because it makes users aware of textual information not available to them through any other means.},
	keywords = {CAMERAS, data mining, handicapped aids, Hardware, Image quality, Internet, Land mobile radio cellular systems, Mobile computing, mobile handsets, mobile text-recognition system, Optical character recognition software, phone-based text-recognition, Product safety, Text recognition, visually-impaired},
	author = {Tudor Dumitras and Lee, M. and Quinones, P. and Smailagic, A. and Siewiorek, Dan and Narasimhan, P.}
}
@conference {12014,
	title = {Integration of visual and inertial information for egomotion: a stochastic approach},
	booktitle = {Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006},
	year = {2006},
	month = {2006/05/15/19},
	pages = {2053 - 2059},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We present a probabilistic framework for visual correspondence, inertial measurements and egomotion. First, we describe a simple method based on Gabor filters to produce correspondence probability distributions. Next, we generate a noise model for inertial measurements. Probability distributions over the motions are then computed directly from the correspondence distributions and the inertial measurements. We investigate combining the inertial and visual information for a single distribution over the motions. We find that with smaller amounts of correspondence information, fusion of the visual data with the inertial sensor results in much better egomotion estimation. This is essentially because inertial measurements decrease the "translation-rotation" ambiguity. However, when more correspondence information is used, this ambiguity is reduced to such a degree that the inertial measurements provide negligible improvement in accuracy. This suggests that inertial and visual information are more closely integrated in a compositional sense},
	keywords = {Computer vision, data mining, Distributed computing, egomotion estimation, Gabor filters, Gravity, inertial information, inertial sensor, Laboratories, Motion estimation, Noise measurement, Probability distribution, probability distributions, Rotation measurement, stochastic approach, Stochastic processes, visual information},
	isbn = {0-7803-9505-0},
	doi = {10.1109/ROBOT.2006.1642007},
	author = {Domke, J. and Aloimonos, J.}
}
@article {17272,
	title = {Knowledge discovery in high-dimensional data: case studies and a user survey for the rank-by-feature framework},
	journal = {IEEE Transactions on Visualization and Computer Graphics},
	volume = {12},
	year = {2006},
	month = {2006/06//May},
	pages = {311 - 322},
	abstract = {Knowledge discovery in high-dimensional data is a challenging enterprise, but new visual analytic tools appear to offer users remarkable powers if they are ready to learn new concepts and interfaces. Our three-year effort to develop versions of the hierarchical clustering explorer (HCE) began with building an interactive tool for exploring clustering results. It expanded, based on user needs, to include other potent analytic and visualization tools for multivariate data, especially the rank-by-feature framework. Our own successes using HCE provided some testimonial evidence of its utility, but we felt it necessary to get beyond our subjective impressions. This paper presents an evaluation of the hierarchical clustering explorer (HCE) using three case studies and an e-mail user survey (n=57) to focus on skill acquisition with the novel concepts and interface for the rank-by-feature framework. Knowledgeable and motivated users in diverse fields provided multiple perspectives that refined our understanding of strengths and weaknesses. A user survey confirmed the benefits of HCE, but gave less guidance about improvements. Both evaluations suggested improved training methods},
	keywords = {case study, Computer aided software engineering, Computer Society, Data analysis, data mining, data visualisation, Data visualization, database management systems, e-mail user survey, Genomics, Helium, Hierarchical Clustering Explorer, hierarchical clustering explorer., high-dimensional data, Histograms, Information visualization evaluation, interactive systems, interactive tool, knowledge discovery, multivariate data, Rank-by-feature framework, Scattering, Testing, user interface, User interfaces, user survey, visual analytic tools, visual analytics, visualization tools},
	isbn = {1077-2626},
	doi = {10.1109/TVCG.2006.50},
	author = {Seo,Jinwook and Shneiderman, Ben}
}
@conference {13849,
	title = {Reranking for Sentence Boundary Detection in Conversational Speech},
	booktitle = {2006 IEEE International Conference on Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings},
	volume = {1},
	year = {2006},
	month = {2006/05/14/19},
	pages = {I-I - I-I},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We present a reranking approach to sentence-like unit (SU) boundary detection, one of the EARS metadata extraction tasks. Techniques for generating relatively small n-best lists with high oracle accuracy are presented. For each candidate, features are derived from a range of information sources, including the output of a number of parsers. Our approach yields significant improvements over the best performing system from the NIST RT-04F community evaluation},
	keywords = {Automatic speech recognition, conversational speech, data mining, Ear, EARS metadata extraction tasks, Feature extraction, hidden Markov models, meta data, Model driven engineering, NIST, NIST RT-04F community evaluation, oracle accuracy, performance evaluation, reranking, sentence-like unit boundary detection, Speech processing, Speech recognition, Telephony},
	isbn = {1-4244-0469-X},
	doi = {10.1109/ICASSP.2006.1660078},
	author = {Roark,B. and Liu,Yang and Harper,M. and Stewart,R. and Lease,M. and Snover,M. and Shafran,I. and Dorr, Bonnie J and Hale,J. and Krasnyanskaya,A. and Yung,L.}
}
@conference {18649,
	title = {A Statistical Analysis of Attack Data to Separate Attacks},
	year = {2006},
	month = {2006/06//},
	pages = {383 - 392},
	abstract = {This paper analyzes malicious activity collected from a test-bed, consisting of two target computers dedicated solely to the purpose of being attacked, over a 109 day time period. We separated port scans, ICMP scans, and vulnerability scans from the malicious activity. In the remaining attack data, over 78\% (i.e., 3,677 attacks) targeted port 445, which was then statistically analyzed. The goal was to find the characteristics that most efficiently separate the attacks. First, we separated the attacks by analyzing their messages. Then we separated the attacks by clustering characteristics using the K-Means algorithm. The comparison between the analysis of the messages and the outcome of the K-Means algorithm showed that 1) the mean of the distributions of packets, bytes and message lengths over time are poor characteristics to separate attacks and 2) the number of bytes, the mean of the distribution of bytes and message lengths as a function of the number packets are the best characteristics for separating attacks},
	keywords = {attack data statistical analysis, attack separation, computer crime, Data analysis, data mining, ICMP scans, K-Means algorithm, pattern clustering, port scans, statistical analysis, vulnerability scans},
	doi = {10.1109/DSN.2006.9},
	author = {Michel Cukier and Berthier,R. and Panjwani,S. and Tan,S.}
}
@article {16949,
	title = {A telescope for high-dimensional data},
	journal = {Computing in Science \& Engineering},
	volume = {8},
	year = {2006},
	month = {2006/04//March},
	pages = {48 - 53},
	abstract = {Muscular dystrophy is a degenerative disease that destroys muscles and ultimately kills its victims. Researchers worldwide are racing to find a cure by trying to uncover the genetic processes that cause it. Given that a key process is muscle development, researchers at a consortium of 10 institutions are studying 1,000 men and women, ages 18 to 40 years, to see how their muscles enlarge with exercise. The 150 variables collected for each participant will make this data analysis task challenging for users of traditional statistical software tools. However, a new approach to visual data analysis is helping these researchers speed up their work. At the University of Maryland{\textquoteright}s Human-Computer Interaction Library, we developed an interactive approach to let researchers explore high-dimensional data in an orderly manner, focusing on specific features one at a time. The rank-by-feature framework lets them adjust controls to specify what they{\textquoteright}re looking for, and then, with only a glance, they can spot strong relationships among variables, find tight data clusters, or identify unexpected gaps. Sometimes surprising outliers invite further study as to whether they represent errors or an unusual outcome. Similar data analysis problems come up in meteorology, finance, chemistry, and other sciences in which complex relationships among many variables govern outcomes. The rank-by-feature framework could be helpful to many researchers, engineers, and managers because they can then steer their analyses toward the action},
	keywords = {Chemistry, Data analysis, data mining, data visualisation, degenerative disease, Degenerative diseases, diseases, Finance, genetic process, Genetics, high-dimensional data, interactive data analysis, medical computing, Meteorology, muscle, muscle development, Muscles, muscular dystrophy, Rank-by-feature framework, software, software libraries, software tools, Telescopes, visual data, visual data analysis},
	isbn = {1521-9615},
	doi = {10.1109/MCSE.2006.21},
	author = {Shneiderman, Ben}
}
@conference {14442,
	title = {Is there a grand challenge or X-prize for data mining?},
	booktitle = {Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining},
	series = {KDD {\textquoteright}06},
	year = {2006},
	month = {2006///},
	pages = {954 - 956},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {This panel will discuss possible exciting and motivating Grand Challenge problems for Data Mining, focusing on bioinformatics, multimedia mining, link mining, text mining, and web mining.},
	keywords = {Bioinformatics, data mining, grand challenge, image mining, link mining, multimedia mining, text mining, video mining, web mining, X-prize},
	isbn = {1-59593-339-5},
	doi = {10.1145/1150402.1150535},
	url = {http://doi.acm.org/10.1145/1150402.1150535},
	author = {Piatetsky-Shapiro,Gregory and Grossman,Robert and Djeraba,Chabane and Feldman,Ronen and Getoor, Lise and Zaki,Mohammed}
}
@conference {11908,
	title = {Pedestrian classification from moving platforms using cyclic motion pattern},
	booktitle = {IEEE International Conference on Image Processing, 2005. ICIP 2005},
	volume = {2},
	year = {2005},
	month = {2005/09//},
	pages = {II- 854-7 - II- 854-7},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {This paper describes an efficient pedestrian detection system for videos acquired from moving platforms. Given a detected and tracked object as a sequence of images within a bounding box, we describe the periodic signature of its motion pattern using a twin-pendulum model. Then a principle gait angle is extracted in every frame providing gait phase information. By estimating the periodicity from the phase data using a digital phase locked loop (dPLL), we quantify the cyclic pattern of the object, which helps us to continuously classify it as a pedestrian. Past approaches have used shape detectors applied to a single image or classifiers based on human body pixel oscillations, but ours is the first to integrate a global cyclic motion model and periodicity analysis. Novel contributions of this paper include: i) development of a compact shape representation of cyclic motion as a signature for a pedestrian, ii) estimation of gait period via a feedback loop module, and iii) implementation of a fast online pedestrian classification system which operates on videos acquired from moving platforms.},
	keywords = {compact shape representation, cyclic motion pattern, data mining, Detectors, digital phase locked loop, digital phase locked loops, feedback loop module, gait analysis, gait phase information, human body pixel oscillations, HUMANS, image classification, Image motion analysis, image representation, image sequence, Image sequences, Motion detection, Object detection, pedestrian classification, pedestrian detection system, Phase estimation, Phase locked loops, principle gait angle, SHAPE, tracking, Videos},
	isbn = {0-7803-9134-9},
	doi = {10.1109/ICIP.2005.1530190},
	author = {Yang Ran and Qinfen Zheng and Weiss, I. and Davis, Larry S. and Abd-Almageed, Wael and Liang Zhao}
}
@article {18462,
	title = {Processing of reverberant speech for time-delay estimation},
	journal = {IEEE Transactions on Speech and Audio Processing},
	volume = {13},
	year = {2005},
	month = {2005/11//},
	pages = {1110 - 1118},
	abstract = {In this paper, we present a method of extracting the time-delay between speech signals collected at two microphone locations. Time-delay estimation from microphone outputs is the first step for many sound localization algorithms, and also for enhancement of speech. For time-delay estimation, speech signals are normally processed using short-time spectral information (either magnitude or phase or both). The spectral features are affected by degradations in speech caused by noise and reverberation. Features corresponding to the excitation source of the speech production mechanism are robust to such degradations. We show that these source features can be extracted reliably from the speech signal. The time-delay estimate can be obtained using the features extracted even from short segments (50-100 ms) of speech from a pair of microphones. The proposed method for time-delay estimation is found to perform better than the generalized cross-correlation (GCC) approach. A method for enhancement of speech is also proposed using the knowledge of the time-delay and the information of the excitation source.},
	keywords = {Acoustic noise, acoustic signal processing, array signal processing, data mining, Degradation, delay estimation, Feature extraction, Hilbert envelope, localization algorithm, microphone arrays, microphone location, Microphones, Phase estimation, reverberation, short-time spectral information, Signal processing, source features, source information excitation, speech enhancement, Speech processing, speech production mechanism, speech signal, time-delay, time-delay estimation},
	isbn = {1063-6676},
	doi = {10.1109/TSA.2005.853005},
	author = {Yegnanarayana,B. and Prasanna,S. R.M and Duraiswami, Ramani and Zotkin,Dmitry N}
}
@conference {14341,
	title = {Seeking the source: software source code as a social and technical artifact},
	booktitle = {Proceedings of the 2005 international ACM SIGGROUP conference on Supporting group work},
	series = {GROUP {\textquoteright}05},
	year = {2005},
	month = {2005///},
	pages = {197 - 206},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	keywords = {data mining, social networks, socio-technical systems, software repositories},
	isbn = {1-59593-223-2},
	doi = {10.1145/1099203.1099239},
	url = {http://doi.acm.org/10.1145/1099203.1099239},
	author = {de Souza,Cleidson and Jon Froehlich and Dourish,Paul}
}
@conference {16944,
	title = {A Rank-by-Feature Framework for Unsupervised Multidimensional Data Exploration Using Low Dimensional Projections},
	booktitle = {IEEE Symposium on Information Visualization, 2004. INFOVIS 2004},
	year = {2004},
	month = {2004///},
	pages = {65 - 72},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Exploratory analysis of multidimensional data sets is challenging because of the difficulty in comprehending more than three dimensions. Two fundamental statistical principles for the exploratory analysis are (1) to examine each dimension first and then find relationships among dimensions, and (2) to try graphical displays first and then find numerical summaries (D.S. Moore, (1999). We implement these principles in a novel conceptual framework called the rank-by-feature framework. In the framework, users can choose a ranking criterion interesting to them and sort 1D or 2D axis-parallel projections according to the criterion. We introduce the rank-by-feature prism that is a color-coded lower-triangular matrix that guides users to desired features. Statistical graphs (histogram, boxplot, and scatterplot) and information visualization techniques (overview, coordination, and dynamic query) are combined to help users effectively traverse 1D and 2D axis-parallel projections, and finally to help them interactively find interesting features},
	keywords = {axis-parallel projections, boxplot, color-coded lower-triangular matrix, computational complexity, computational geometry, Computer displays, Computer science, Computer vision, Data analysis, data mining, data visualisation, Data visualization, Displays, dynamic query, Educational institutions, exploratory data analysis, feature detection, feature detection/selection, Feature extraction, feature selection, graph theory, graphical displays, histogram, Information Visualization, interactive systems, Laboratories, Multidimensional systems, Principal component analysis, rank-by-feature prism, scatterplot, statistical analysis, statistical graphics, statistical graphs, unsupervised multidimensional data exploration, very large databases},
	isbn = {0-7803-8779-3},
	doi = {10.1109/INFVIS.2004.3},
	author = {Seo,J. and Shneiderman, Ben}
}
@conference {15840,
	title = {The effect of bilingual term list size on dictionary-based cross-language information retrieval},
	booktitle = {Proceedings of the 36th Annual Hawaii International Conference on System Sciences, 2003},
	year = {2003},
	month = {2003/01/06/9},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Bilingual term lists are extensively used as a resource for dictionary-based cross-language information retrieval (CLIR), in which the goal is to find documents written in one natural language based on queries that are expressed in another. This paper identifies eight types of terms that affect retrieval effectiveness in CLIR applications through their coverage by general-purpose bilingual term lists, and reports results from an experimental evaluation of the coverage of 35 bilingual term lists in news retrieval application. Retrieval effectiveness was found to be strongly influenced by term list size for lists that contain between 3,000 and 30,000 unique terms per language. Supplemental techniques for named entity translation were found to be useful with even the largest lexicons. The contribution of named-entity translation was evaluated in a cross-language experiment involving English and Chinese. Smaller effects were observed from deficiencies in the coverage of domain-specific terminology when searching news stories.},
	keywords = {bilingual term list, Chinese language, Computer science, Control systems, Cross-language information retrieval, data mining, Dictionaries, dictionary-based information retrieval, Educational institutions, English language, Frequency, Information retrieval, language translation, named-entity translation, natural languages, Surface morphology, Terminology},
	isbn = {0-7695-1874-5},
	doi = {10.1109/HICSS.2003.1174250},
	author = {Demner-Fushman,D. and Oard, Douglas}
}
@conference {12000,
	title = {Eye design in the plenoptic space of light rays},
	booktitle = {Ninth IEEE International Conference on Computer Vision, 2003. Proceedings},
	year = {2003},
	month = {2003/10/13/16},
	pages = {1160-1167 vol.2 - 1160-1167 vol.2},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Natural eye designs are optimized with regard to the tasks the eye-carrying organism has to perform for survival. This optimization has been performed by the process of natural evolution over many millions of years. Every eye captures a subset of the space of light rays. The information contained in this subset and the accuracy to which the eye can extract the necessary information determines an upper limit on how well an organism can perform a given task. In this work we propose a new methodology for camera design. By interpreting eyes as sample patterns in light ray space we can phrase the problem of eye design in a signal processing framework. This allows us to develop mathematical criteria for optimal eye design, which in turn enables us to build the best eye for a given task without the trial and error phase of natural evolution. The principle is evaluated on the task of 3D ego-motion estimation.},
	keywords = {3D ego-motion estimation, Assembly, B-splines, Camera design, CAMERAS, captured image, compound eyes, Computer vision, data mining, eye, eye-carrying organism, Eyes, filter optimization, image representation, image resolution, Information geometry, Laboratories, light field reconstruction, light gathering power, light rays, mixed spherical-Cartesian coordinate system, Motion estimation, natural evolution process, natural eye designs, natural image statistics, optical nanotechnology, Optical signal processing, optimal eye design mathematical criteria, Organisms, plenoptic image formation, plenoptic space, plenoptic video geometry, sampling operators, sensory ecology, Signal design, Signal processing, signal processing framework, signal processing tool, square-summable sequences, visual acuity},
	isbn = {0-7695-1950-4},
	doi = {10.1109/ICCV.2003.1238623},
	author = {Neumann, J. and Ferm{\"u}ller, Cornelia and Aloimonos, J.}
}
@book {13691,
	title = {Video Mining},
	year = {2003},
	month = {2003/08/31/},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Video Mining is an essential reference for the practitioners and academicians in the fields of multimedia search engines.Half a terabyte or 9,000 hours of motion pictures are produced around the world every year. Furthermore, 3,000 television stations broadcasting for twenty-four hours a day produce eight million hours per year, amounting to 24,000 terabytes of data. Although some of the data is labeled at the time of production, an enormous portion remains unindexed. For practical access to such huge amounts of data, there is a great need to develop efficient tools for browsing and retrieving content of interest, so that producers and end users can quickly locate specific video sequences in this ocean of audio-visual data.Video Mining is important because it describes the main techniques being developed by the major players in industry and academic research to address this problem. It is the first time research from these leaders in the field developing the next-generation multimedia search engines is being described in great detail and gathered into a single volume.Video Mining will give valuable insights to all researchers and non-specialists who want to understand the principles applied by the multimedia search engines that are about to be deployed on the Internet, in studios{\textquoteright} multimedia asset management systems, and in video-on-demand systems.},
	keywords = {Computers / Client-Server Computing, Computers / Computer Science, Computers / Database Management / Data Mining, Computers / Database Management / General, Computers / Information Technology, Computers / Information Theory, Computers / Intelligence (AI) \& Semantics, Computers / Interactive \& Multimedia, Computers / Networking / General, Computers / Security / Cryptography, data mining, Data mining/ Congresses, Mathematics / General, Medical / General, multimedia systems, Multimedia systems/ Congresses, Technology \& Engineering / Electrical, Technology \& Engineering / Telecommunications},
	isbn = {9781402075490},
	author = {Rosenfeld,Azriel and David Doermann and DeMenthon,Daniel}
}
@conference {17098,
	title = {Dynamic layout management in a multimedia bulletin board},
	booktitle = {IEEE 2002 Symposia on Human Centric Computing Languages and Environments, 2002. Proceedings},
	year = {2002},
	month = {2002///},
	pages = {51 - 53},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {This paper proposes a novel user interface to manage the dynamic layout of multimedia objects in the Multimedia Bulletin Board (MBB) system. The MBB has been designed and implemented as a prototype of an asynchronous communication system that enables rich communication and collaboration among users of multimedia objects such as text, image, moving picture, sound, voice, Web, office document, and other files. The layout properties of the multimedia objects on a board (e.g. x-y position, size, z-order, explicit and implicit links, etc.) show important and useful information on the user dynamics occurring within a board. However, a fixed layout created and edited by multiple users may prevent users from recognizing and identifying other information. This paper resolves this problem with a novel user-controlled layout strategy made visible with dynamic layout templates (DLT). Users can reorganize the objects to extract meaningful information related to time, source, geographic location, or topic.},
	keywords = {Asynchronous communication, asynchronous communication system, Collaboration, data mining, dynamic layout management, dynamic layout templates, groupware, Human computer interaction, image, Information services, Laboratories, moving picture, Multimedia Bulletin Board system, multimedia computing, Multimedia databases, multimedia objects, multimedia systems, office document, Prototypes, sound, text, user interface, User interfaces, user-controlled layout strategy, voice, Web, Web pages},
	isbn = {0-7695-1644-0},
	doi = {10.1109/HCC.2002.1046344},
	author = {Kang,Hyunmo and Shneiderman, Ben and Wolff,G. J}
}
@article {17259,
	title = {Interactively exploring hierarchical clustering results [gene identification]},
	journal = {Computer},
	volume = {35},
	year = {2002},
	month = {2002/07//},
	pages = {80 - 86},
	abstract = {To date, work in microarrays, sequenced genomes and bioinformatics has focused largely on algorithmic methods for processing and manipulating vast biological data sets. Future improvements will likely provide users with guidance in selecting the most appropriate algorithms and metrics for identifying meaningful clusters-interesting patterns in large data sets, such as groups of genes with similar profiles. Hierarchical clustering has been shown to be effective in microarray data analysis for identifying genes with similar profiles and thus possibly with similar functions. Users also need an efficient visualization tool, however, to facilitate pattern extraction from microarray data sets. The Hierarchical Clustering Explorer integrates four interactive features to provide information visualization techniques that allow users to control the processes and interact with the results. Thus, hybrid approaches that combine powerful algorithms with interactive visualization tools will join the strengths of fast processors with the detailed understanding of domain experts},
	keywords = {algorithmic methods, arrays, Bioinformatics, biological data sets, biology computing, Data analysis, data mining, data visualisation, Data visualization, DNA, Fluorescence, gene functions, gene identification, gene profiles, Genetics, Genomics, Hierarchical Clustering Explorer, hierarchical systems, interactive exploration, interactive information visualization tool, interactive systems, Large screen displays, meaningful cluster identification, metrics, microarray data analysis, pattern clustering, pattern extraction, Process control, Sensor arrays, sequenced genomes, Tiles},
	isbn = {0018-9162},
	doi = {10.1109/MC.2002.1016905},
	author = {Seo,Jinwook and Shneiderman, Ben}
}
@conference {16466,
	title = {Optimized seamless integration of biomolecular data},
	booktitle = {Proceedings of the IEEE 2nd International Symposium on Bioinformatics and Bioengineering Conference, 2001},
	year = {2001},
	month = {2001/11/04/6},
	pages = {23 - 32},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Today, scientific data is inevitably digitized, stored in a variety of heterogeneous formats, and is accessible over the Internet. Scientists need to access an integrated view of multiple remote or local heterogeneous data sources. They then integrate the results of complex queries and apply further analysis and visualization to support the task of scientific discovery. Building a digital library for scientific discovery requires accessing and manipulating data extracted from flat files or databases, documents retrieved from the Web, as well as data that is locally materialized in warehouses or is generated by software. We consider several tasks to provide optimized and seamless integration of biomolecular data. Challenges to be addressed include capturing and representing source capabilities; developing a methodology to acquire and represent metadata about source contents and access costs; and decision support to select sources and capabilities using cost based and semantic knowledge, and generating low cost query evaluation plans},
	keywords = {analysis, Bioinformatics, biology computing, cost based knowledge, Costs, Data analysis, data mining, data visualisation, Data visualization, Data warehouses, decision support, digital library, Educational institutions, information resources, Internet, low cost query evaluation plans, Mediation, meta data, metadata, molecular biophysics, multiple local heterogeneous data sources, multiple remote heterogeneous data sources, optimized seamless biomolecular data integration, scientific discovery, scientific information systems, semantic knowledge, software libraries, visual databases, Visualization},
	isbn = {0-7695-1423-5},
	doi = {10.1109/BIBE.2001.974408},
	author = {Eckman,B. A and Lacroix,Z. and Raschid, Louiqa}
}
@conference {12098,
	title = {A trend analysis of exploitations},
	booktitle = {2001 IEEE Symposium on Security and Privacy, 2001. S\&P 2001. Proceedings},
	year = {2001},
	month = {2001///},
	pages = {214 - 229},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {We have conducted an empirical study of a number of computer security exploits and determined that the rates at which incidents involving the exploit are reported to CERT can be modeled using a common mathematical framework. Data associated with three significant exploits involving vulnerabilities in phf, imap, and bind can all be modeled using the formula C=I+S{\texttimes}√M where C is the cumulative count of reported incidents, M is the time since the start of the exploit cycle, and I and S are the regression coefficients determined by analysis of the incident report data. Further analysis of two additional exploits involving vulnerabilities in mountd and statd confirm the model. We believe that the models will aid in predicting the severity of subsequent vulnerability exploitations, based on the rate of early incident reports},
	keywords = {Computer science, computer security exploits, Data analysis, data mining, Educational institutions, exploitations, Performance analysis, Predictive models, Regression analysis, Risk management, security of data, software engineering, system intrusions, System software, trend analysis, vulnerabilities, vulnerability exploitation},
	isbn = {0-7695-1046-9},
	doi = {10.1109/SECPRI.2001.924300},
	author = {Browne,H. K and Arbaugh, William A. and McHugh,J. and Fithen,W. L}
}
@article {17842,
	title = {Visualization of large data sets with the Active Data Repository},
	journal = {IEEE Computer Graphics and Applications},
	volume = {21},
	year = {2001},
	month = {2001/08//Jul},
	pages = {24 - 33},
	abstract = {We implement ray-casting-based volume rendering and isosurface rendering methods using the Active Data Repository (ADR) for visualizing out-of-core data sets. We have developed the ADR object-oriented framework to provide support for applications that employ range queries with user-defined mapping and aggregation operations on large-scale multidimensional data. ADR targets distributed-memory parallel machines with one or more disks attached to each node. It is designed as a set of modular services implemented in C++, which can be customized for application-specific processing. The ADR runtime system supports common operations such as memory management, data retrieval, and scheduling of processing across a parallel machine},
	keywords = {active data repository, ADR runtime system, Algorithm design and analysis, application-specific processing, C++, data mining, data retrieval, data visualisation, Data visualization, distributed-memory parallel machines, Indexing, Information retrieval, isosurface rendering, Isosurfaces, large data sets, large-scale multidimensional data, Memory management, modular services, out-of-core data sets, parallel machine, Parallel machines, Partitioning algorithms, ray-casting-based volume rendering, Rendering (computer graphics), Runtime, software libraries, storage management},
	isbn = {0272-1716},
	doi = {10.1109/38.933521},
	author = {Kurc, T. and Catalyurek,U. and Chang,Chialin and Sussman, Alan and Saltz, J.}
}
@conference {15889,
	title = {Effects of term segmentation on Chinese/English cross-language information retrieval},
	booktitle = {String Processing and Information Retrieval Symposium, 1999 and International Workshop on Groupware},
	year = {1999},
	month = {1999///},
	pages = {149 - 157},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {The majority of recent Cross-Language Information Retrieval (CLIR) research has focused on European languages. CLIR problems that involve East Asian languages such as Chinese introduce additional challenges, because written Chinese texts lack boundaries between terms. The paper examines three Chinese segmentation techniques in combination with two variants of dictionary-based Chinese to English query translation. The results indicate that failure to segment terms, particularly technical terms and names, can have a cascading effect that reduces retrieval effectiveness. Task-tuned segmentation algorithms and alternative term weighting strategies are suggested as productive directions for future work},
	keywords = {alternative term weighting strategies, cascading effect, Chinese segmentation techniques, Chinese/English cross-language information retrieval, Chromium, CLIR problems, Cross-Language Information Retrieval research, data mining, Dictionaries, dictionary-based Chinese, East Asian languages, English query translation, European languages, future work, Information retrieval, language translation, linguistics, natural language processing, natural languages, productive directions, Reactive power, retrieval effectiveness, task-tuned segmentation algorithms, technical terms, term segmentation, text analysis, written Chinese texts},
	isbn = {0-7695-0268-7},
	doi = {10.1109/SPIRE.1999.796590},
	author = {Oard, Douglas and Wang,Jianqiang}
}
@article {15705,
	title = {A semidiscrete matrix decomposition for latent semantic indexing information retrieval},
	journal = {ACM Trans. Inf. Syst.},
	volume = {16},
	year = {1998},
	month = {1998/10//},
	pages = {322 - 346},
	abstract = {The vast amount of textual information available today is useless unless it can be effectively and efficiently searched. The goal in information retrieval is to find documents that are relevant to a given user query. We can represent and document collection by a matrix whose (i, j) entry is nonzero only if the ith term appears in the jth document; thus each document corresponds to a columm vector. The query is also represented as a column vector whose ith term is nonzero only if the ith term appears in the query. We score each document for relevancy by taking its inner product with the query. The highest-scoring documents are considered the most relevant. Unfortunately, this method does not necessarily retrieve all relevant documents because it is based on literal term matching.  Latent semantic indexing (LSI) replaces the document matrix with an approximation generated by the truncated singular-value decomposition (SVD). This method has been shown to overcome many difficulties associated with literal term matching. In this article we propose replacing the SVD with the semidiscrete decomposition (SDD). We will describe the SDD approximation, show how to compute it, and compare the SDD-based LSI method to the SVD-based LSI methods. We will show that SDD-based LSI does as well as SVD-based LSI in terms of document retrieval while requiring only one-twentieth the storage and one-half the time to compute each query. We will also show how to update the SDD approximation when documents are added or deleted from the document collection.},
	keywords = {data mining, latent semantic indexing, semidiscrete decomposition, singular-value decomposition, text retrieval},
	isbn = {1046-8188},
	doi = {10.1145/291128.291131},
	url = {http://doi.acm.org/10.1145/291128.291131},
	author = {Kolda,Tamara G. and O{\textquoteright}Leary, Dianne P.}
}
@conference {16499,
	title = {Wrapper generation for Web accessible data sources},
	booktitle = {3rd IFCIS International Conference on Cooperative Information Systems, 1998. Proceedings},
	year = {1998},
	month = {1998/08/22/22},
	pages = {14 - 23},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {There is an increase in the number of data sources that can be queried across the WWW. Such sources typically support HTML forms-based interfaces and search engines query collections of suitably indexed data. The data is displayed via a browser: One drawback to these sources is that there is no standard programming interface suitable for applications to submit queries. Second, the output (answer to a query) is not well structured. Structured objects have to be extracted from the HTML documents which contain irrelevant data and which may be volatile. Third, domain knowledge about the data source is also embedded in HTML documents and must be extracted. To solve these problems, we present technology to define and (automatically) generate wrappers for Web accessible sources. Our contributions are as follows: (1) Defining a wrapper interface to specify the capability of Web accessible data sources. (2) Developing a wrapper generation toolkit of graphical interfaces and specification languages to specify the capability of sources and the functionality of the wrapper (3) Developing the technology to automatically generate a wrapper appropriate to the Web accessible source, from the specifications.},
	keywords = {application program interfaces, data mining, Databases, Educational institutions, Electrical capacitance tomography, HTML, HTML documents, Internet, Query processing, Read only memory, Search engines, Specification languages, Uniform resource locators, World Wide Web, wrapper generation toolkit, WWW},
	isbn = {0-8186-8380-5},
	doi = {10.1109/COOPIS.1998.706180},
	author = {Gruser,J. and Raschid, Louiqa and Vidal,M. E and Bright,L.}
}
@conference {17412,
	title = {The eyes have it: a task by data type taxonomy for information visualizations},
	booktitle = {, IEEE Symposium on Visual Languages, 1996. Proceedings},
	year = {1996},
	month = {1996/09/03/6},
	pages = {336 - 343},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A useful starting point for designing advanced graphical user interfaces is the visual information seeking Mantra: overview first, zoom and filter, then details on demand. But this is only a starting point in trying to understand the rich and varied set of information visualizations that have been proposed in recent years. The paper offers a task by data type taxonomy with seven data types (one, two, three dimensional data, temporal and multi dimensional data, and tree and network data) and seven tasks (overview, zoom, filter, details-on-demand, relate, history, and extracts)},
	keywords = {advanced graphical user interface design, Art, data mining, data type taxonomy, data visualisation, Data visualization, Displays, Eyes, Graphical user interfaces, Information filtering, Information filters, information visualizations, multi dimensional data, Multimedia databases, network data, Taxonomy, visual databases, visual information seeking, visual programming},
	isbn = {0-8186-7508-X},
	doi = {10.1109/VL.1996.545307},
	author = {Shneiderman, Ben}
}
@conference {17335,
	title = {Query previews in networked information systems},
	booktitle = {Proceedings of the Third Forum on Research and Technology Advances in Digital Libraries, 1996. ADL {\textquoteright}96},
	year = {1996},
	month = {1996/05/13/15},
	pages = {120 - 129},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {In a networked information system (such as the NASA Earth Observing System-Data Information System (EOS-DIS)), there are three major obstacles facing users in a querying process: network performance, data volume and data complexity. In order to overcome these obstacles, we propose a two phase approach to query formulation. The two phases are the Query Preview and the Query Refinement. In the Query Preview phase, users formulate an initial query by selecting rough attribute values. The estimated number of matching data sets is shown, graphically on preview bars which allows users to rapidly focus on a manageable number of relevant data sets. Query previews also prevent wasted steps by eliminating zero hit queries. When the estimated number of data sets is long enough, the initial query is submitted to the network which returns the metadata of the data sets for further refinement in the Query Refinement phase. The two phase approach to query formulation overcomes slow network performance, and reduces the data volume and data complexity, problems. This approach is especially appropriate for users who do not have extensive knowledge about the data and who prefer an exploratory method to discover data patterns and exceptions. Using this approach, we have developed dynamic query user interfaces to allow users to formulate their queries across a networked environment},
	keywords = {Computer networks, data complexity, data mining, data patterns, data volume, dynamic query user interfaces, Educational institutions, EOS-DIS, exploratory method, Information retrieval, Information services, Information systems, Intelligent networks, interactive systems, Laboratories, Manipulator dynamics, matching data sets, NASA Earth Observing System-Data Information System, Network performance, networked environment, networked information systems, query formulation, query preview, query refinement, querying process, rough attribute values, User interfaces, visual databases, zero hit queries},
	isbn = {0-8186-7403-2},
	doi = {10.1109/ADL.1996.502522},
	author = {Donn,K. and Plaisant, Catherine and Shneiderman, Ben}
}
@conference {14169,
	title = {Hierarchical curve representation},
	booktitle = {, 11th IAPR International Conference on Pattern Recognition, 1992. Vol.III. Conference C: Image, Speech and Signal Analysis, Proceedings},
	year = {1992},
	month = {1992/09/30/Aug-3},
	pages = {143 - 146},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {Presents a robust method for describing planar curves in multiple resolution using curvature information. The method is developed by taking into account the discrete nature of digital images as well as the discrete aspect of a multiresolution structure (pyramid). The authors deal with the robustness of the technique, which is due to the additional information that is extracted from observing the behavior of corners in the pyramid. Furthermore the resulting algorithm is conceptually simple and easily parallelizable. They develop theoretical results, analyzing the curvature of continuous curves in scale-space, which show the behavior of curvature extrema under varying scale. These results are used to eliminate any ambiguities that might arise from sampling problems due to the discreteness of the representation. Finally, experimental results demonstrate the potential of the method},
	keywords = {Automation, continuous curves, curvature, data mining, digital images, Educational institutions, Feature extraction, hierarchical curve representation, IMAGE PROCESSING, image recognition, image resolution, Image segmentation, multiresolution structure, Object recognition, planar curves, pyramid, Robustness, Sampling methods, Smoothing methods},
	isbn = {0-8186-2920-7},
	doi = {10.1109/ICPR.1992.201947},
	author = {Ferm{\"u}ller, Cornelia and Kropatsch,W.}
}
@conference {18307,
	title = {3D object recognition via simulated particles diffusion},
	booktitle = {IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1989. Proceedings CVPR {\textquoteright}89},
	year = {1989},
	month = {1989/06//},
	pages = {442 - 449},
	publisher = {IEEE},
	organization = {IEEE},
	abstract = {A novel approach for 3D object recognition is presented. This approach is model-based, and assumes either 3D or 21/2 D scene acquisition. Transformation detection is accomplished along with an object identification (six degrees of freedom, three rotational and three translational, are assumed). The diffusion-like simulation recently introduced as a means for characterization of shape is used in the extraction of point features. The point features represent regions on the object{\textquoteright}s surface that are extreme in curvature (i.e. concavities and convexities). Object matching is carried out by examining the correspondence between the object{\textquoteright}s set of point features and the model{\textquoteright}s set of point features, using an alignment strategy. Triangles are constructed between all possible triples of object{\textquoteright}s point features, and then are aligned to candidate corresponding triangles of the model{\textquoteright}s point features. 21/2 range images are transformed into a volumetric representation through a parallel projection onto the 3-D space. The resultant volume is suitable for processing by the diffusion-like simulation},
	keywords = {3D object recognition, alignment strategy, Computational modeling, Computer science, data mining, Gold, Layout, Noise shaping, Object detection, Object recognition, parallel projection, pattern recognition, point features, radio access networks, scene acquisition, shape characterisation, Shape measurement, simulated particles diffusion, transformation detection},
	isbn = {0-8186-1952-x},
	doi = {10.1109/CVPR.1989.37886},
	author = {Yacoob,Yaser and Gold,Y. I}
}
