Querying and clustering Web pages about persons and organizations

by: S Ye, TS Chua, JR Kei

Web Intelligence, 2003. WI 2003. Proceedings. IEEE/WIC International Conference on (2003), pp. 344-350.

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Abstract

One of the most frequent Web surfing tasks is to search for names of persons and organizations. Such names are often not distinctive, commonly occurring, and nonunique. Thus, a single name may be mapped to several entities. We describe a methodology to cluster the Web pages returned by the search engine so that pages belonging to different entities are clustered into different groups. The algorithm uses a combination of named entities, link-based and structure-based information as features to partition the document set into direct and indirect pages using a decision model. It then uses the distinct direct pages as seeds to cluster the document set into different clusters. The algorithm has been found to be effective for Web-based applications.

@inproceedings{citeulike:447616, abstract = {One of the most frequent Web surfing tasks is to search for names of persons and organizations. Such names are often not distinctive, commonly occurring, and nonunique. Thus, a single name may be mapped to several entities. We describe a methodology to cluster the Web pages returned by the search engine so that pages belonging to different entities are clustered into different groups. The algorithm uses a combination of named entities, link-based and structure-based information as features to partition the document set into direct and indirect pages using a decision model. It then uses the distinct direct pages as seeds to cluster the document set into different clusters. The algorithm has been found to be effective for Web-based applications.}, author = {Ye, S. and Chua, T. S. and Kei, J. R. }, citeulike-article-id = {447616}, journal = {Web Intelligence, 2003. WI 2003. Proceedings. IEEE/WIC International Conference on}, keywords = {clustering, web}, pages = {344--350}, posted-at = {2005-12-23 10:03:49}, priority = {2}, title = {Querying and clustering Web pages about persons and organizations}, url = {http://ieeexplore.ieee.org/xpls/abs\_all.jsp?arnumber=1241214}, year = {2003} }

RIS record

TY - CONF ID - citeulike:447616 L3 - citeulike-article-id:447616 TI - Querying and clustering Web pages about persons and organizations JF - Web Intelligence, 2003. WI 2003. Proceedings. IEEE/WIC International Conference on SP - 344 EP - 350 N2 - One of the most frequent Web surfing tasks is to search for names of persons and organizations. Such names are often not distinctive, commonly occurring, and nonunique. Thus, a single name may be mapped to several entities. We describe a methodology to cluster the Web pages returned by the search engine so that pages belonging to different entities are clustered into different groups. The algorithm uses a combination of named entities, link-based and structure-based information as features to partition the document set into direct and indirect pages using a decision model. It then uses the distinct direct pages as seeds to cluster the document set into different clusters. The algorithm has been found to be effective for Web-based applications. KW - clustering KW - web AU - Ye, S AU - Chua, TS AU - Kei, JR PY - 2003/// UR - http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=1241214 ER -

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