期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：8
出版社：S&S Publications
摘要：Search engines return roughly the same results for the same query, regardless of the user’s realinterest. Personalized search is an important research area that aims to resolve the ambiguity of query terms. Toincrease the relevance of search results, personalized search engines create user profiles to capture the users’personal preferences and as such identify the actual goal of the input query. Since users are usually reluctant toexplicitly provide their preferences due to the extra manual effort involved, recent research has focused on theautomatic learning of user preferences from users’ search histories or browsed documents and the development ofpersonalized systems based on the learned user preferences. In this project, we focus on search enginepersonalization and develop several concept-based user profiling methods that are based on both positive andnegative preferences. User profiles which capture both the user’s positive and negative preferences. Negativepreferences improve the separation of similar and dissimilar queries, which facilitates an agglomerative clusteringalgorithm to decide if the optimal clusters have been obtained
