Understanding Rule Behavior through Apriori Algorithm over Social Network Data

Dr. S.S.Phulari; Dr.S.D.Khamitkar

Understanding Rule Behavior through Apriori Algorithm over Social Network Data

Dr. S.S.Phulari * §

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Dr.S.D.Khamitkar

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§ S.R.T.M.University , Nanded, MS, India.

Understanding Rule Behavior through Apriori Algorithm over Social Network Data

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Abstract

APRIORI algorithm is a popular data mining technique used for extracting hidden patterns from data. This paper highlights practical demonstration of this algorithm for association rule mining over a survey data set of students related to social network usage. We concluded with discussions on the number of research observations including new rules generated during the process.

Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr. S.S.Phulari, Dr.S.D.Khamitkar. 2012. "Understanding Rule Behavior through Apriori Algorithm over Social Network Data". Global Journal of Computer Science and Technology, Global Journal of Computer Science and Technology - C: Software & Data Engineering GJCST-C Volume 12 (GJCST Volume 12 Issue C10).

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GJCST Volume 12 Issue C10

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords

Not Found

Classification

GJCST-C Classification E.m

Submission ReceivedDecember 7, 2011
Peer Review Double Blind
Handling Editor
Accepted January 1, 2012
Published January 15, 2012

Version of record

v1.2

Issue date

June 7, 2012

Language

English

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Article Matrices

Total Score: 154

Country: India

Subject: Global Journal of Computer Science and Technology

Authors: Dr. S.S.Phulari , P.U.Bhalchandra, Dr.S.D.Khamitkar, S.N.Lokhande (PhD/Dr. count: 2)

View Count (all-time): 381

Total Views (Real + Logic): 3324

Total Downloads (simulated): 144

Publish Date: 2012 01, Sun

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Total Views: 3.3K

Total Downloads: 144

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