Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks Export

@incollection{Kim_AWMWUA_2006, abstract = {Personalized web search incorporates an individual user's interests when deciding relevant results to return. While, most web search engines are usually designed to serve all users, without considering the interests of individual users. We propose a method to (re)rank the results from a search engine using a learned user profile, called a user interest hierarchy (UIH), from web pages that are of interest to the user. The user's interest in web pages will be determined implicitly, without directly asking the user. Experimental results indicate that our personalized ranking methods, when used with a popular search engine, can yield more potentially interesting web pages for individual users.}, author = {Kim, Hyoung-Rae and Chan, Philip}, citeulike-article-id = {3890096}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/11891321_9}, citeulike-linkout-1 = {http://www.springerlink.com/content/6132721146710566}, doi = {10.1007/11891321_9}, journal = {Advances in Web Mining and Web Usage Analysis}, keywords = {2get, bookmarks, context, contextualir, ir, personalization, ranking}, pages = {158--176}, posted-at = {2009-09-07 23:10:06}, priority = {2}, title = {Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks}, url = {http://dx.doi.org/10.1007/11891321_9}, year = {2006} }

TY - CHAP ID - Kim_AWMWUA_2006 L3 - citeulike-article-id:3890096 N2 - Personalized web search incorporates an individual user’s interests when deciding relevant results to return. While, most web search engines are usually designed to serve all users, without considering the interests of individual users. We propose a method to (re)rank the results from a search engine using a learned user profile, called a user interest hierarchy (UIH), from web pages that are of interest to the user. The user’s interest in web pages will be determined implicitly, without directly asking the user. Experimental results indicate that our personalized ranking methods, when used with a popular search engine, can yield more potentially interesting web pages for individual users. JF - Advances in Web Mining and Web Usage Analysis EP - 176 TI - Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks SP - 158 KW - 2get KW - bookmarks KW - context KW - contextualir KW - ir KW - personalization KW - ranking AU - Kim, Hyoung-Rae AU - Chan, Philip PY - 2006/// UR - http://dx.doi.org/10.1007/11891321_9 ER -