Query-log based Authority Analysis for Web Information Search Export

@inproceedings{LuxenburgerW04, abstract = {The ongoing explosion of web information calls for more intelligent and personalized methods towards better search result quality for advanced queries. Query logs and click streams obtained from web browsers or search engines can contribute to better quality by exploiting the collaborative recommendations that are implicitly embedded in this information. This paper presents a new method that incorporates the notion of query nodes into the PageRank model and integrates the implicit relevance feedback given by click streams into the automated process of authority analysis. This approach generalizes the well-known random-surfer model into a random-expert model that mimics the behavior of an expert user in an extended session consisting of queries, query refinements, and result-navigation steps. The enhanced PageRank scores, coined QRank scores, can be computed offline; at query-time they are combined with query-specific relevance measures with virtually no overhead. Our preliminary experiments, based on real-life query-log and click-stream traces from eight different trial users indicate significant improvements in the precision of search results.}, address = {Brisbane, Australia}, author = {Luxenburger, Julia and Weikum, Gerhard}, booktitle = {Web information systems, WISE 2004 : 5th International Conference on Web Information Systems Engineering ; Brisbane, Australia, November 22-24, 2004 ; proceedings}, citeulike-article-id = {1338871}, citeulike-linkout-0 = {http://www.delis.upb.de/paper/DELIS-TR-0137.pdf}, editor = {Zhou, Xiaofang and Su, Stanley Y. W. and Papazoglou, Mike P. and Orlowska, Maria E. and Jeffery, Keith G.}, keywords = {clickstream\_data, query-expansion}, pages = {90--101}, posted-at = {2007-05-28 17:52:44}, priority = {0}, publisher = {Springer}, series = {Lecture Notes in Computer Science}, title = {Query-log based Authority Analysis for Web Information Search}, url = {http://www.delis.upb.de/paper/DELIS-TR-0137.pdf}, volume = {3306}, year = {2004} }

TY - CONF ID - LuxenburgerW04 L3 - citeulike-article-id:1338871 N2 - The ongoing explosion of web information calls for more intelligent and personalized methods towards better search result quality for advanced queries. Query logs and click streams obtained from web browsers or search engines can contribute to better quality by exploiting the collaborative recommendations that are implicitly embedded in this information. This paper presents a new method that incorporates the notion of query nodes into the PageRank model and integrates the implicit relevance feedback given by click streams into the automated process of authority analysis. This approach generalizes the well-known random-surfer model into a random-expert model that mimics the behavior of an expert user in an extended session consisting of queries, query refinements, and result-navigation steps. The enhanced PageRank scores, coined QRank scores, can be computed offline; at query-time they are combined with query-specific relevance measures with virtually no overhead. Our preliminary experiments, based on real-life query-log and click-stream traces from eight different trial users indicate significant improvements in the precision of search results. SE - Lecture Notes in Computer Science AD - Brisbane, Australia EP - 101 TI - Query-log based Authority Analysis for Web Information Search PB - Springer VL - 3306 T2 - Web information systems, WISE 2004 : 5th International Conference on Web Information Systems Engineering ; Brisbane, Australia, November 22-24, 2004 ; proceedings SP - 90 KW - clickstream_data KW - query-expansion AU - Luxenburger, Julia AU - Weikum, Gerhard A2 - Zhou, Xiaofang A2 - Su, Stanley A2 - Papazoglou, Mike A2 - Orlowska, Maria A2 - Jeffery, Keith PY - 2004/// UR - http://www.delis.upb.de/paper/DELIS-TR-0137.pdf ER -