@conference {14404,
	title = {GeoDDupe: A Novel Interface for Interactive Entity Resolution in Geospatial Data},
	booktitle = {Information Visualization, 2007. IV {\textquoteright}07. 11th International Conference},
	year = {2007},
	month = {2007/07//},
	pages = {489 - 496},
	abstract = {Due to the growing interest in geospatial data mining and analysis, data cleaning and integration in geospatial data is becoming an important issue. Geospatial entity resolution is the process of reconciling multiple location references to the same real world location within a single data source (deduplication) or across multiple data sources (integration). In this paper, we introduce an interactive tool called GeoDDupe which effectively combines automatic data mining algorithms for geospatial entity resolution with a novel network visualization supporting users{\textquoteright} resolution analysis and decisions. We illustrate the GeoDDupe interface with an example geospatial dataset and show how users can efficiently and accurately resolve location entities. Finally, the case study with two real-world geospatial datasets demonstrates the potential of GeoDDupe.},
	keywords = {algorithms;data, cleaning;geospatial, data, entity, GeoDDupe;automatic, interfaces;, mining, mining;geography;user, mining;geospatial, resolution;interactive, tool;network, visualization;data},
	doi = {10.1109/IV.2007.55},
	author = {Kang,Hyunmo and Sehgal,V. and Getoor, Lise}
}
@conference {14498,
	title = {D-Dupe: An Interactive Tool for Entity Resolution in Social Networks},
	booktitle = {Visual Analytics Science And Technology, 2006 IEEE Symposium On},
	year = {2006},
	month = {2006/11/31/2},
	pages = {43 - 50},
	abstract = {Visualizing and analyzing social networks is a challenging problem that has been receiving growing attention. An important first step, before analysis can begin, is ensuring that the data is accurate. A common data quality problem is that the data may inadvertently contain several distinct references to the same underlying entity; the process of reconciling these references is called entity-resolution. D-Dupe is an interactive tool that combines data mining algorithms for entity resolution with a task-specific network visualization. Users cope with complexity of cleaning large networks by focusing on a small subnetwork containing a potential duplicate pair. The subnetwork highlights relationships in the social network, making the common relationships easy to visually identify. D-Dupe users resolve ambiguities either by merging nodes or by marking them distinct. The entity resolution process is iterative: as pairs of nodes are resolved, additional duplicates may be revealed; therefore, resolution decisions are often chained together. We give examples of how users can flexibly apply sequences of actions to produce a high quality entity resolution result. We illustrate and evaluate the benefits of D-Dupe on three bibliographic collections. Two of the datasets had already been cleaned, and therefore should not have contained duplicates; despite this fact, many duplicates were rapidly identified using D-Dupe{\textquoteright}s unique combination of entity resolution algorithms within a task-specific visual interface},
	keywords = {algorithm;data, analysis;social, computing;user, D-Dupe, interactive, interface;data, interfaces;, mining, mining;interactive, network, problem;entity, QUALITY, resolution;entity-resolution;social, sciences, systems;social, tool;data, visual, visualization;task-specific},
	doi = {10.1109/VAST.2006.261429},
	author = {Bilgic,M. and Licamele,L. and Getoor, Lise and Shneiderman, Ben}
}
@conference {14961,
	title = {Efficient techniques for range search queries on earth science data},
	booktitle = {Scientific and Statistical Database Management, 2002. Proceedings. 14th International Conference on},
	year = {2002},
	month = {2002///},
	pages = {142 - 151},
	abstract = {We consider the problem of organizing large scale earth science raster data to efficiently handle queries for identifying regions whose parameters fall within certain range values specified by the queries. This problem seems to be critical to enabling basic data mining tasks such as determining associations between physical phenomena and spatial factors, detecting changes and trends, and content based retrieval. We assume that the input is too large to fit in internal memory and hence focus on data structures and algorithms that minimize the I/O bounds. A new data structure, called a tree-of-regions (ToR), is introduced and involves a combination of an R-tree and efficient representation of regions. It is shown that such a data structure enables the handling of range queries in an optimal I/O time, under certain reasonable assumptions. We also show that updates to the ToR can be handled efficiently. Experimental results for a variety of multi-valued earth science data illustrate the fast execution times of a wide range of queries, as predicted by our theoretical analysis.},
	keywords = {based, computing;, content, data, data;, databases;, Earth, factors;, large, mining, mining;, natural, processing;, queries;, query, range, raster, retrieval;, scale, Science, sciences, search, spatial, structures;, tasks;, temporal, tree, tree-of-regions;, visual},
	doi = {10.1109/SSDM.2002.1029714},
	author = {Shi,Qingmin and JaJa, Joseph F.}
}
