NDLI: Mining associations by pattern structure in large relational tables

Content Provider	IEEE Xplore Digital Library
Author	Haixun Wang Chang-Shing Perng Sheng Ma Yu, P.S.
Copyright Year	2002
Description	Author affiliation: IBM T. J. Watson Res. Center, Yorktown Heights, NY, USA (Haixun Wang; Chang-Shing Perng; Sheng Ma; Yu, P.S.)
Abstract	Association rule mining aims at discovering patterns whose support is beyond a given threshold. Mining patterns composed of items described by an arbitrary subset of attributes in a large relational table represents a new challenge and has various practical applications, including the event management systems that motivated this work. The attribute combinations that define the items in a pattern provide the structural information of the pattern. Current association algorithms do not make full use of the structural information of the patterns: the information is either lost after it is encoded with attribute values, or is constrained by a given hierarchy or taxonomy. Pattern structures convey important knowledge about the patterns. We present an architecture that organizes the mining space based on pattern structures. By exploiting the interrelationships among pattern structures, execution times for mining can be reduced significantly. This advantage is demonstrated by our experiments using both synthetic and real-life datasets.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Pattern Analysis & Machine Intelligence (TCPAMI) IEEE Comput. Soc. Tech. Committee on Computational Intelligence (TCCI)
Starting Page	482
Ending Page	489
File Size	492957
Page Count	8
File Format	PDF
ISBN	0769517544
DOI	10.1109/ICDM.2002.1183992
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-12-09
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Data mining Itemsets Data security Authorization Zinc Association rules History Filters Software algorithms Algorithm design and analysis
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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