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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α Kurukshetra University

Data Mining Based on Semantic Similarity to mine new Association Rules

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References

7 Cites in Article

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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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Not applicable for this article.

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
Pg. 11- 17

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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): 264

Total Views (Real + Logic): 10159

Total Downloads (simulated): 2625

Publish Date: 2012 08, Tue

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Total Views: 10159

Total Downloads: 2625

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