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：7
页码：13144-13150
出版社：IJECS
摘要：In this paper I propose a method that, given a query submitted to a search engine, suggests a list of related queries.Query recommendation is a method to improve search results in web. This paper presents a method for mining searchengine query logs to obtain fast query recommendation on a large scale. Search engines generally return long list ofranked pages, finding the important information related to a particular topic is becoming increasingly difficult andtherefore, optimized search engines become one of the most popular solution available. In this work, an algorithm hasbeen applied to recommend related queries to a query submitted by user. For this, the technology used for allowingquery recommendations is query log which contains attributes like query name, clicked URL, rank, time. Then, thesimilarity based on keywords as well as clicked URL’s is calculated. Additionally, clusters have been obtained bycombining the similarities of both keywords and clicked URL’s. The related queries are based in previously issuedqueries The method not only discovers the related queries, but also ranks them according to a relevance criterion. Inthis paper the rank is updated only the clicked URL, not all the related URL’s of the page
关键词：Query Log; Search Engine; and Query;Clustering; Query Similarity; Information Retrieval; Page;Rank Updater.
