AN EMPIRICAL STUDY OF VARIOUS FREQUENT ITEM SET MINING TECHNIQUES

Utkarsh Kumar Shrivastava

AN EMPIRICAL STUDY OF VARIOUS FREQUENT ITEM SET MINING TECHNIQUES

Authors: Utkarsh Kumar Shrivastava

Unique Paper ID: 147526
Volume: 5
Issue: 8
PageNo: 249-252

Keywords: Data Mining Frequent Pattern Mining Support Confidence Apriori DIC Partitioning.

Abstract:
Frequent item set mining has been a heart favorite theme for data mining researchers for over a decade. A large amount of literature has been dedicated to this research and tremendous progress has been made, ranging from efficient and scalable algorithms for frequent itemset mining in transaction databases to numerous research frontiers, such as sequential pattern mining, structured pattern mining, correlation mining, associative classification, and frequent pattern-based clustering, as well as their broad applications. In this paper, a literature review of various latest techniques for mining frequent items from a transaction data base are presented in critical manner,

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Cite This Article

ISSN: 2349-6002
Volume: 5
Issue: 8
PageNo: 249-252

AN EMPIRICAL STUDY OF VARIOUS FREQUENT ITEM SET MINING TECHNIQUES

Available:https://ijirt.org/Article?manuscript=147526

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Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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