On a combination of probabilistic and boolean ir models for WWW document retrieval

  • Authors:

  • Masaharu Yoshioka;Makoto Haraguchi

  • Affiliations:

  • Hokkaido University, Hokkaido, Japan;Hokkaido University, Hokkaido, Japan

  • Venue:
  • ACM Transactions on Asian Language Information Processing (TALIP)
  • Year:
  • 2005

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Abstract

Even though a Boolean query can express the information need precisely enough to select relevant documents, it is not easy to construct an appropriate Boolean query that covers all relevant documents. To utilize a Boolean query effectively, a mechanism to retrieve as many as possible relevant documents is therefore required. In accordance with this requirement, we propose a method for modifying a given Boolean query by using information from a relevant document set. The retrieval results, however, may deteriorate if some important query terms are removed by this reformulation. A further mechanism is thus required in order to use other query terms that are useful for finding more relevant documents, but are not strictly required in relevant documents. To meet this requirement, we propose a new method that combines the probabilistic IR and the Boolean IR models. We also introduce a new IR system---called appropriate Boolean query reformulation for information retrieval (ABRIR)---based on these two methods and the Okapi system. ABRIR uses both a word index and a phrase index formed from combinations of two adjacent noun words. The effectiveness of these two methods was confirmed according to the NTCIR-4 Web test collection.