TY - CONF T1 - EventGraphs: Charting Collections of Conference Connections T2 - 2011 44th Hawaii International Conference on System Sciences (HICSS) Y1 - 2011 A1 - Hansen,D. A1 - Smith,M. A A1 - Shneiderman, Ben KW - conference connections KW - Conferences KW - Data visualization KW - EventGraphs KW - hashtag KW - measurement KW - Media KW - message identification KW - multimedia computing KW - NodeXL KW - Real time systems KW - social media network diagrams KW - social networking (online) KW - Twitter AB - EventGraphs are social media network diagrams of conversations related to events, such as conferences. Many conferences now communicate a common "hashtag" or keyword to identify messages related to the event. EventGraphs help make sense of the collections of connections that form when people follow, reply or mention one another and a keyword. This paper defines EventGraphs, characterizes different types, and shows how the social media network analysis add-in NodeXL supports their creation and analysis. The structural patterns to look for in EventGraphs are highlighted and design ideas for their improvement are discussed. JA - 2011 44th Hawaii International Conference on System Sciences (HICSS) PB - IEEE SN - 978-1-4244-9618-1 M3 - 10.1109/HICSS.2011.196 ER - TY - CONF T1 - The evolution of stochastic grammars for representation and recognition of activities in videos T2 - 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops) Y1 - 2011 A1 - Chellapa, Rama KW - activity recognition KW - activity representation KW - Conferences KW - Educational institutions KW - Grammar KW - Image analysis KW - image recognition KW - image representation KW - image understanding KW - pattern recognition KW - stochastic image grammars KW - syntactic pattern recognition methods KW - video signal processing KW - video understanding KW - Videos AB - The speaker is one of the privileged many to have been taught syntactic pattern recognition methods by the Late Prof. K.S. Fu. In this talk, I will discuss the evolution of stochastic image grammars from the early seventies to now with a focus on image and video understanding applications. JA - 2011 IEEE International Conference on Computer Vision Workshops (ICCV Workshops) PB - IEEE SN - 978-1-4673-0062-9 M3 - 10.1109/ICCVW.2011.6130309 ER - TY - CONF T1 - Variable remapping of images from very different sources T2 - 2011 18th IEEE International Conference on Image Processing (ICIP) Y1 - 2011 A1 - Wei Zhang A1 - Yanlin Guo A1 - Meth, R. A1 - Sokoloff, H. A1 - Pope, A. A1 - Strat, T. A1 - Chellapa, Rama KW - automatic object identification KW - Buildings KW - CAMERAS KW - Conferences KW - constrained motion estimation KW - coordinates system KW - Estimation KW - G-RANSAC framework KW - image context enlargement KW - Image Enhancement KW - image registration KW - image sequence registration KW - Image sequences KW - Motion estimation KW - Robustness KW - temporal integration KW - variable image remapping AB - We present a system which registers image sequences acquired by very different sources, so that multiple views could be transformed to the same coordinates system. This enables the functionality of automatic object identification and confirmation across views and platforms. The capability of the system comes from three ingredients: 1) image context enlargement through temporal integration; 2) robust motion estimation using the G-RANSAC framework with a relaxed correspondence criteria; 3) constrained motion estimation within the G-RANSAC framework. The proposed system has worked successfully on thousands of frames from multiple collections with significant variations in scale and resolution. JA - 2011 18th IEEE International Conference on Image Processing (ICIP) PB - IEEE SN - 978-1-4577-1304-0 M3 - 10.1109/ICIP.2011.6115729 ER - TY - CONF T1 - Rigorous Probabilistic Trust-Inference with Applications to Clustering T2 - IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09 Y1 - 2009 A1 - DuBois,Thomas A1 - Golbeck,Jennifer A1 - Srinivasan, Aravind KW - Clustering algorithms KW - Conferences KW - Educational institutions KW - Extraterrestrial measurements KW - Inference algorithms KW - Intelligent agent KW - random graphs KW - Social network services KW - trust inferrence KW - Visualization KW - Voting KW - Web sites AB - The World Wide Web has transformed into an environment where users both produce and consume information. In order to judge the validity of information, it is important to know how trustworthy its creator is. Since no individual can have direct knowledge of more than a small fraction of information authors, methods for inferring trust are needed. We propose a new trust inference scheme based on the idea that a trust network can be viewed as a random graph, and a chain of trust as a path in that graph. In addition to having an intuitive interpretation, our algorithm has several advantages, noteworthy among which is the creation of an inferred trust-metric space where the shorter the distance between two people, the higher their trust. Metric spaces have rigorous algorithms for clustering, visualization, and related problems, any of which is directly applicable to our results. JA - IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technologies, 2009. WI-IAT '09 PB - IEEE VL - 1 SN - 978-0-7695-3801-3 M3 - 10.1109/WI-IAT.2009.109 ER - TY - CONF T1 - Representing Tuple and Attribute Uncertainty in Probabilistic Databases T2 - Seventh IEEE International Conference on Data Mining Workshops, 2007. ICDM Workshops 2007 Y1 - 2007 A1 - Sen,P. A1 - Deshpande, Amol A1 - Getoor, Lise KW - attribute uncertainty KW - Computer science KW - Conferences KW - correlation structures KW - data mining KW - Data models KW - database management systems KW - Educational institutions KW - inference mechanisms KW - noisy data sources KW - probabilistic database KW - probabilistic inference KW - Probability distribution KW - Query processing KW - Relational databases KW - Sensor phenomena and characterization KW - tuple representation KW - Uncertainty KW - uncertainty handling AB - 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. JA - Seventh IEEE International Conference on Data Mining Workshops, 2007. ICDM Workshops 2007 PB - IEEE SN - 978-0-7695-3019-2 M3 - 10.1109/ICDMW.2007.11 ER - TY - JOUR T1 - Human-centered computing, online communities, and virtual environments JF - IEEE Computer Graphics and Applications Y1 - 1999 A1 - Brown,J. R A1 - van Dam,A. A1 - Earnshaw,R. A1 - Encarnacao,J. A1 - Guedj,R. A1 - Preece,J. A1 - Shneiderman, Ben A1 - Vince,J. KW - Books KW - Collaboration KW - Collaborative work KW - Conferences KW - EC/NSF joint Advanced Research Workshop KW - Feeds KW - Human computer interaction KW - human-centered computing KW - Internet KW - Joining materials KW - Laboratories KW - Online communities KW - Research initiatives KW - USA Councils KW - User interfaces KW - Virtual environment KW - virtual environments KW - Virtual reality AB - This report summarizes results of the first EC/NSF joint Advanced Research Workshop, which identified key research challenges and opportunities in information technology. The group agreed that the first joint research workshop should concentrate on the themes of human-centered computing and VEs. Human-centered computing is perceived as an area of strategic importance because of the move towards greater decentralization and decomposition in the location and provision of computation. The area of VEs is one where increased collaboration should speed progress in solving some of the more intractable problems in building effective applications VL - 19 SN - 0272-1716 CP - 6 M3 - 10.1109/38.799742 ER -