Automatic categorization of query results

  • Authors:
  • Kaushik Chakrabarti;Surajit Chaudhuri;Seung-won Hwang

  • Affiliations:
  • Microsoft Research;Microsoft Research;University of Illinois

  • Venue:
  • SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
  • Year:
  • 2004

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Abstract

Exploratory ad-hoc queries could return too many answers - a phenomenon commonly referred to as "information overload". In this paper, we propose to automatically categorize the results of SQL queries to address this problem. We dynamically generate a labeled, hierarchical category structure - users can determine whether a category is relevant or not by examining simply its label; she can then explore just the relevant categories and ignore the remaining ones, thereby reducing information overload. We first develop analytical models to estimate information overload faced by a user for a given exploration. Based on those models, we formulate the categorization problem as a cost optimization problem and develop heuristic algorithms to compute the min-cost categorization.