Article

Mining and processing category ranking

Authors:

Seung-won Hwang,

Hwanjo YuAuthors Info & Claims

SAC '07: Proceedings of the 2007 ACM symposium on Applied computing

Pages 441 - 442

https://doi.org/10.1145/1244002.1244103

Published: 11 March 2007 Publication History

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Abstract

As more and more data are becoming accessible, a naive retrieval of such data may often result in too many answers, as we commonly call "information overload".

References

[1]

Ronald Fagin. Combining fuzzy information from multiple systems. In PODS, 1996.

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[2]

Ronald Fagin, Amnon Lotem, and Moni Naor. Optimal aggregation algorithms for middleware. In PODS, 2001.

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[3]

Kevin C. Chang and Seung-won Hwang. Minimal probing: Supporting expensive predicates for top-k queries. In SIGMOD, 2002.

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[4]

Seung-won Hwang. Optimizing ranked retrieval over categorical attributes. In CBMS, 2006.

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[5]

Hwanjo Yu, Seung-won Hwang, and Kevin Chang. RankFP: A framework for supporting rank formulation and processing. In ICDE, 2005.

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M. Kendall. Rank Correlation Methods. Hafner, 1955.

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Cited By

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Park SSong JLee JLee WRee S(2015)How to measure similarity for multiple categorical data sets?Multimedia Tools and Applications10.1007/s11042-014-1914-574:10(3489-3505)Online publication date: 1-May-2015
https://dl.acm.org/doi/10.1007/s11042-014-1914-5
Lee WSong JLeung C(2011)Categorical data skyline using classification treeProceedings of the 13th Asia-Pacific web conference on Web technologies and applications10.5555/1996794.1996818(181-187)Online publication date: 18-Apr-2011
https://dl.acm.org/doi/10.5555/1996794.1996818
Lee WSong JLeung C(2011)Categorical Data Skyline Using Classification TreeWeb Technologies and Applications10.1007/978-3-642-20291-9_19(181-187)Online publication date: 2011
https://doi.org/10.1007/978-3-642-20291-9_19

Index Terms

Mining and processing category ranking
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
  2. Information retrieval
    1. Evaluation of retrieval results
    2. Retrieval models and ranking
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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Published In

SAC '07: Proceedings of the 2007 ACM symposium on Applied computing

March 2007

1688 pages

ISBN:1595934804

DOI:10.1145/1244002

Conference Chairs:
Yookun Cho
Seoul National University, Seoul, Korea
,
Roger L. Wainwright
University of Tulsa, Tulsa, Oklahoma
,
Hisham M. Haddad
Kennesaw State University, Kennesaw, Georgia
,
Sung Y. Shin
South Dakota State University, Brookings, South Dakota
,
Program Chair:
Yong Wan Koo
The University of Suwon, Gyeongggi-do, Korea

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 11 March 2007

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March 11 - 15, 2007

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Park SSong JLee JLee WRee S(2015)How to measure similarity for multiple categorical data sets?Multimedia Tools and Applications10.1007/s11042-014-1914-574:10(3489-3505)Online publication date: 1-May-2015
https://dl.acm.org/doi/10.1007/s11042-014-1914-5
Lee WSong JLeung C(2011)Categorical data skyline using classification treeProceedings of the 13th Asia-Pacific web conference on Web technologies and applications10.5555/1996794.1996818(181-187)Online publication date: 18-Apr-2011
https://dl.acm.org/doi/10.5555/1996794.1996818
Lee WSong JLeung C(2011)Categorical Data Skyline Using Classification TreeWeb Technologies and Applications10.1007/978-3-642-20291-9_19(181-187)Online publication date: 2011
https://doi.org/10.1007/978-3-642-20291-9_19

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Efficient Top-k Query Answering through its Top-N Rewritings Using Views

Supporting ad-hoc ranking aggregates

Efficient processing of exact top-k queries over disk-resident sorted lists

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