Automatic Categorization of Query Results

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.

• Type: Conference
• Year: 2004
• Where: SIGMOD
• Authors: Kaushik Chakrabarti, Surajit Chaudhuri, Seung-won Hwang
• Keywords: Cost Optimization Problem, Database, Exploratory Ad-hoc Queries, Information Overload, SIGMOD 2004