Automatic boolean query suggestion for professional search

  • Authors:

  • Youngho Kim;Jangwon Seo;W. Bruce Croft

  • Affiliations:

  • University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA;University of Massachusetts Amherst, Amherst, MA, USA

  • Venue:
  • Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

In professional search environments, such as patent search or legal search, search tasks have unique characteristics: 1) users interactively issue several queries for a topic, and 2) users are willing to examine many retrieval results, i.e., there is typically an emphasis on recall. Recent surveys have also verified that professional searchers continue to have a strong preference for Boolean queries because they provide a record of what documents were searched. To support this type of professional search, we propose a novel Boolean query suggestion technique. Specifically, we generate Boolean queries by exploiting decision trees learned from pseudo-labeled documents and rank the suggested queries using query quality predictors. We evaluate our algorithm in simulated patent and medical search environments. Compared with a recent effective query generation system, we demonstrate that our technique is effective and general.