Facets extraction-based approach for query recommendation using data mining approach

Abstract

Search engines are popularly utilized for extracting desired information from World Wide Web by users. Efficiency of these search engines are dependent on how fast search results can be retrieved and whether these results reflects the desired info or not. For a particular query, vast amount of relevant information is scattered across the multiple web pages. Search engines generate multiple web links as a output. It has been a jigsaw puzzle for users to identify and select relevant links to extract further desired information. To address this issue, we are proposing an approach for Query Recommendation for getting relevant search results from web using facet mining techniques. Facets are the semantically related words for a query which defines its multiple aspects. We are extracting these aspects of a query from Wikipedia pages which is considered to be a trustworthy resource on the web. Our proposed system uses various text processing techniques to refine the results using lexical resource like WorldNet. In this paper we are discussing our approach and its implementation and results obtained. In the paper , Discussion on future research direction is included to conclude.