Scalable Link Mining and Analysis on Information Networks

author: Philip S. Yu, Department of Computer Science, College of Engineering, University of Illinois at Chicago
published: Sept. 18, 2009,   recorded: July 2009,   views: 4275


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With the ubiquity of information networks and their broad applications, there have been numerous studies on the construction, online analytical processing, and mining of information networks in multiple disciplines, including social network analysis, World-Wide Web, database systems, data mining, machine learning, and networked communication and information systems. Algorithms like PageRank and HITS have been developed in late 1990s to explore links among Web pages to discover authoritative pages and hubs. Links have also been popularly used in citation analysis and social network analysis. However, there is a lack of systematic treatment on how to fully explore the power of links in scalable data analysis. In this talk, the power of links are examined in details to improve the effectiveness and efficiency of typical data analysis tasks, including information integration, on-line analytic processing, and other interesting data mining tasks, especially in the multi-relational databases and/or the World-Wid e Web environments.

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