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國立雲林科技大學 National Yunlin University of Science and Technology N.Y.U.S.T. I. M. Interactive visualization for opportunistic exploration of large document collections Presenter : Chun-Ping Wu Authors :Simon Lehmann, Ulrich Schwanecke, Ralf Dorner IS 2010 1 Intelligent Database Systems Lab Outline Motivation Objective Methodology Experiments Conclusion Comments N.Y.U.S.T. I. M. 2 Intelligent Database Systems Lab Motivation N.Y.U.S.T. I. M. Finding relevant information in a large and comprehensive collection of cross-referenced documents like Wikipedia usually requires a quite accurate idea where to look for the pieces of data being sought. 3 Intelligent Database Systems Lab Objective N.Y.U.S.T. I. M. This paper describes the interactive visualization Wivi which enables users to intuitively navigate Wikipedia by visualizing the structure of visited articles and emphasizing relevant other topics. 4 Intelligent Database Systems Lab Methodology N.Y.U.S.T. I. M. The current Degree of interest(DOI) of an article v: A-priori-importance(API) of the unvisited articles can be formally defined as The temporal distance D of an unvisited article v can then be defined as 5 Intelligent Database Systems Lab Methodology N.Y.U.S.T. I. M. The architecture of Wivi. 6 Intelligent Database Systems Lab Experiments N.Y.U.S.T. I. M. 7 Intelligent Database Systems Lab Experiments N.Y.U.S.T. I. M. 8 Intelligent Database Systems Lab Conclusion N.Y.U.S.T. I. M. The approach combines both a visualization of visited articles and articles that could be immediately reached from all visited articles. It also calculates a degree of interest of the unvisited articles based on the structure and history of the article graph. 9 Intelligent Database Systems Lab Comments Advantage The system is very interesting. The approach can help users more easily to read. Drawback N.Y.U.S.T. I. M. When a large amount of data, the system performance is poor. Application Browsing, Searching 10 Intelligent Database Systems Lab