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Vague Query Responder

Semantic Web and Knowledge Services   Social Software  

Bookshop owners can outperform Amazon and Google when the queries are vague - so can our software

Although today's web search engines are very powerful, they still fail to provide intuitively relevant results for many types of queries, especially ones that are vaguely-formed in the user's own mind. We argue that associations between terms in a search query can reveal the underlying information needs in the users' mind and should be taken into account in search. Our initial experimental results on a corpus of 500 books from Amazon shows that our approach can find the right books for users given authentic vague queries, even in those cases where Google and Amazon's own book search fail.

Participant: Dawei Song, Jianhan Zhu, Marc Eisenstadt, Chris Denham



URL: http://kmi.open.ac.uk/projects/vqr/