期刊名称：International Journal of Engineering and Computer Science
印刷版ISSN：2319-7242
出版年度：2015
卷号：4
期号：6
页码：12877-12883
出版社：IJECS
摘要：Search Engines generally provide long lists of ranked pages, finding the desired information contentfrom which is typical on the user end and therefore, Search Result Optimization techniques comeinto play. The proposed system based on learning from query logs predicts user information needsand reduces the seek time of the user within the search result list.To achieve this, the method first mines the logs using a similarity function to perform queryclustering and then discovers the sequential order of clicked URLs in each cluster . Finally, searchresult list is optimized by re-ranking the pages. The proposed system proves to be efficient as theuser desired relevant pages occupy their places earlier in the result list and thus reducing the searchspace. This thesis also presents a query recommendation scheme towards better informationretrieval.
关键词：World Wide Web (WWW); Information Retrieval; Search Engine; Query processing
