Tensor query expansion: A cognitively motivated relevance model
Michael Edward Symonds, Peter Bruza, Laurianne Sitbon, Ian Turner · QUT ePrints (Queensland University of Technology) · 2011
In information retrieval, a user's query is often not a complete representation of their real information need. The user's information need is a cognitive construction, however the use of cognitive models to perform query expansion have had little study. In this paper, we present a cognitively motivated query expansion technique that uses semantic features for use in ad hoc retrieval. This model is evaluated against a state-of-the-art query expansion technique. The results show our approach provides significant improvements in retrieval effectiveness for the TREC data sets tested.