Query Expansion Using Term Distribution and Term Association
Dipasree Pal, Mandar Mitra, Samar Bhattacharya · 2018
Good term selection is an important issue for an automatic query expansion (AQE) technique. AQE techniques that select expansion terms from the target corpus usually do so in one of two ways. Distribution based term selection methods typically compute the divergence between the distribution of a term in the (pseudo) relevant documents with that in the whole corpus (or a random distribution). Association based term selection, on the other hand, uses information about how a candidate term co-occurs with the original query terms. Our goal in this study is to investigate how these two classes of methods may be combined to improve retrieval effectiveness. We propose the following combination-based approach. Candidate expansion terms are first obtained using a distribution based method. This set is then refined based on the strength of the association of terms with the original query terms. We test our methods on several TREC collections. The proposed combinations generally yield better results than each individual method, and are comparable to AQE approaches such as RM3. En route to our primary goal, we also propose some modifications to an existing AQE method which lead to improved performance