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.
|Number of pages||12|
|Journal||Proceedings of the ACM SIGMOD International Conference on Management of Data|
|Publication status||Published - 2004 Jul 27|
|Event||Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2004 - Paris, France|
Duration: 2004 Jun 13 → 2004 Jun 18
All Science Journal Classification (ASJC) codes
- Information Systems