Automatic Query Reweighting Using co-occurrence Graphs

TitleAutomatic Query Reweighting Using co-occurrence Graphs
Publication TypeConference Paper
Year of Publication2019
AuthorsAklouche, B, Bounhas, I, Slimani, Y
Conference Name16th Applied Computing conference, Cagliari, Italy, November 7-9, 2019
KeywordsAd-Hoc Information Retrieval., BM25, Co-occurrence graph, Query Reformulation, Query Reweighting, Term’s Discriminative Power
Abstract

Providing a relevant and valid response to the user has always been challenging. Query reformulation methods have been widely applied in an attempt to provide a better representation of the user’s query and thus improve retrieval performance. In this paper, we present a new query reweighting method for document retrieval based on term co-occurrence graphs, which are built using a context window-based approach over the entire corpus. We propose an adapted version of the well-established Okapi BM25 model that allows identifying the most informative terms in the query and assigning them optimal weights. This measure stands out by its ability to evaluate the discriminative power of terms from co-occurrence graphs. Experimental results on two standard ad-hoc TREC collections show that our method improves both retrieval effectiveness and robustness and outperforms the state-of-the-art baselines with significant margins.

Add new comment

Plain text

  • No HTML tags allowed.
  • Web page addresses and e-mail addresses turn into links automatically.
  • Lines and paragraphs break automatically.