@inproceedings{chakrabarti2004automatic,
author = {Chakrabarti, Kaushik and Chaudhuri, Surajit and Hwang, Seung-won},
title = {Automatic Categorization of Query Results},
booktitle = {ACM SIGMOD Conference},
year = {2004},
month = {January},
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.},
url = {http://approjects.co.za/?big=en-us/research/publication/automatic-categorization-of-query-results/},
edition = {ACM SIGMOD Conference},
}