Predicting the Cumulative Effect of Multiple Query Formulations

  • Authors:
  • Isak Taksa

  • Affiliations:
  • Baruch College, CUNY

  • Venue:
  • ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02
  • Year:
  • 2005

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Abstract

Multiple query formulations (MQF) have been extensively explored and when used, provide considerable improvements in quality of information retrieval on the Web. However, the question of how to formulate a variety of distinctive queries and how many queries are needed in each unique case remains essentially unanswered. In this research we present a process for selecting search terms and formulating multiple short queries from the original long query. We introduce a Scaled Cumulative Query Weight (驴) function which is based exclusively on the submitted long query. We demonstrate that this function can serve as a predictive variable for the effectiveness of various multiple query formulation methods and can be used algorithmically to determine the operational parameters for a multiple query formulation process.