A recommender system approach to enhance web search and query formulation

While search engines are the primary means by which information is located online, significant issues remain when trying to satisfy the needs of searchers, especially in the face of the type of vague queries
that dominate Web search. In this paper, we tackle this problem by applying a recommender system approach to Web search which allows users to dynamically interact with the result-space that is of interest to them. Our proposed recommendation interface also facilitates query expansion through a context-sensitive tag cloud, helping searchers to efficiently assimilate potential expansion terms that are mined from results of interest. We present findings from a live user trial of our approach which indicate, for example, that it facilitates users to locate relevant information more quickly when compared to using standard search engine result lists.