Data Mining Based on Semantic Similarity to mine new Association Rules

Data Mining Based on Semantic Similarity to mine new Association Rules

Aakanksha Mahajan

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Dr. Sandeep Jain

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Kurukshetra University

Data Mining Based on Semantic Similarity to mine new Association Rules

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References

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W Au,K Chan (1998). An effective algorithm for discovering fuzzy rules in relational databases.
W Au,K Chan (1999). FARM: a data mining system for discovering fuzzy association rules.
J Han,M Kamber (2001). Data Mining -Concepts and Techniques.
G Chen,Q Wei (2002). Fuzzy association rules and the extended mining algorithms.
X Unknown Title.
Xindong Wu,Chengqi Zhang,Shichao Zhang (2002). Efficient mining of both positive and negative association rules.
Tzung-Pei Hong,Kuei-Ying Lin,Shyue-Liang Wang (2006). Mining fuzzy sequential patterns from quantitative transactions.

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

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No ethics committee approval was required for this article type.

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How to Cite This Article

Aakanksha Mahajan. 2012. \u201cData Mining Based on Semantic Similarity to mine new Association Rules\u201d. Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 12 (GJCST Volume 12 Issue C12).

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GJCST Volume 12 Issue C12

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Association Rules Confidence Data mining Fuzzy logic Semantic similarity Support

Submission ReceivedDecember 13, 2011
Peer Review Double Blind
Handling Editor
Accepted January 5, 2012
Published January 15, 2012

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v1.2

Issue date

August 21, 2012

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Article Matrices

Total Score: 107

Country: India

Subject: Global Journal of Computer Science and Technology - C: Software & Data Engineering

Authors: Dr. Sandeep Jain, Aakanksha Mahajan (PhD/Dr. count: 1)

View Count (all-time): 286

Total Views (Real + Logic): 10206

Total Downloads (simulated): 2541

Publish Date: 2012 08, Tue

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Total Views: 10206

Total Downloads: 2541

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