A SURVEY ON: INFERRING USER SEARCH GOALS ENGINE THROUGH IMAGE CLICK THROUGH DATA

Abstract

Different users may have different search goals when they submit broad-topic and ambiguous query, to a search engine. The inference and analysis of user search goals can be very useful in improving performance of search engine. To infer user search goals by analyzing search engine query logs a novel approach is proposed. First, we propose a framework to find out different user search goals for a query by clustering the proposed feedback sessions. Second, we propose a novel approach to generate pseudo-documents by using feedback sessions for clustering. Thus the project focuses on combine approach of web usage mining and web content mining to improve the search engine results by inferring user search goals. In the proposed work a new approach is introduced to re-order the search results based on the contents and user interest rather than keyword and page ranking provided by search engines. This paper presents a survey on inferring the user meant image retrieval under user feedback information.