@inproceedings{775c3ac4a4404073b26eea3a9b4eaefb,
title = "Getting critical categories of a data set",
abstract = "Ranking query that is widely used in various applications is a fundamental kind of queries in the database management field. Although most of the existing work on ranking query focuses on getting top-k high-score tuples from a data set, this paper focuses on getting top-k critical categories from a data set, where each category is a data item in the nominal attribute or a combination of data items from more than one nominal attribute. To describe each category precisely, we use a data distribution that comes from the score attribute to represent each category, so that the set consisting of all categories can be treated as a probabilistic data set. In this paper, we devise a novel method to handle this issue. Analysis in theorem and experimental results show the effectiveness and efficiency of the proposed method.",
keywords = "critical category, possible world, ranking query",
author = "Cheqing Jin and Yizhen Zhang and Aoying Zhou",
year = "2011",
doi = "10.1007/978-3-642-23535-1\_16",
language = "英语",
isbn = "9783642235344",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "169--180",
booktitle = "Web-Age Information Management - 12th International Conference,WAIM 2011, Proceedings",
note = "12th International Conference on Web-Age Information Management, WAIM 2011 ; Conference date: 14-09-2011 Through 16-09-2011",
}