Simulation of Within-Session Query Variations Using a Text Segmentation Approach

Abstract. We propose a generative model for automatic query reformulations from an initial query using the underlying subtopic structure of top ranked retrieved documents. We address three types of query reformulations a) specialization; b) generalization; and c) drift. To test our model we generate the three reformulation variants starting with selected fields from the TREC-8 topics as the initial queries. We use manual judgments from multiple assessors to calculate the accuracy of the reformulated query variants and observe accuracies of 65%, 82% and 69% respectively for specialization, generalization and drift reformulations.

• Type: Journal
• Year: 2011
• Where: CLEF
• Authors: Debasis Ganguly, Johannes Leveling, Gareth J. F. Jones
• Keywords: Automatic Query, CLEF 2011, Generative Model, Information Technology, Subtopic Structure