TY - JOUR T1 - Interactive Entity Resolution in Relational Data: A Visual Analytic Tool and Its Evaluation JF - IEEE Transactions on Visualization and Computer Graphics Y1 - 2008 A1 - Kang,Hyunmo A1 - Getoor, Lise A1 - Shneiderman, Ben A1 - Bilgic,M. A1 - Licamele,L. KW - algorithms KW - Computer Graphics KW - D-Dupe KW - data visualisation KW - database management systems KW - Databases, Factual KW - graphical user interface KW - Graphical user interfaces KW - human-centered computing KW - Image Interpretation, Computer-Assisted KW - Information Storage and Retrieval KW - Information Visualization KW - interactive entity resolution KW - relational context visualization KW - Relational databases KW - relational entity resolution algorithm KW - User interfaces KW - user-centered design KW - User-Computer Interface KW - visual analytic tool AB - Databases often contain uncertain and imprecise references to real-world entities. Entity resolution, the process of reconciling multiple references to underlying real-world entities, is an important data cleaning process required before accurate visualization or analysis of the data is possible. In many cases, in addition to noisy data describing entities, there is data describing the relationships among the entities. This relational data is important during the entity resolution process; it is useful both for the algorithms which determine likely database references to be resolved and for visual analytic tools which support the entity resolution process. In this paper, we introduce a novel user interface, D-Dupe, for interactive entity resolution in relational data. D-Dupe effectively combines relational entity resolution algorithms with a novel network visualization that enables users to make use of an entity's relational context for making resolution decisions. Since resolution decisions often are interdependent, D-Dupe facilitates understanding this complex process through animations which highlight combined inferences and a history mechanism which allows users to inspect chains of resolution decisions. An empirical study with 12 users confirmed the benefits of the relational context visualization on the performance of entity resolution tasks in relational data in terms of time as well as users' confidence and satisfaction. VL - 14 SN - 1077-2626 CP - 5 M3 - 10.1109/TVCG.2008.55 ER -