UGC Approved Journal no 63975

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 5 Issue 7
July-2018
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRC006303


Registration ID:
184605

Page Number

1750-1756

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Title

A Survey on an effective incremental mining algorithm for frequent item-sets with big data based on MapReduce framework

Abstract

Due to the increasing use of very large databases and data warehouses, mining useful information and helpful knowledge from transactions is evolving into an important research area. Thus, most of the classic algorithms proposed focused on batch mining, and did not utilize previously mined information in incrementally growing databases. In the past, researchers usually assumed databases were static to simplify data mining problems. This research presents a new scalable algorithm Delta+ for discovering closed frequent item sets. Exploits a divide-and-conquer approach. Adopts several optimizations aimed to save both space and time in computing item set closures and their supports. Propose a new effective and memory-efficient pruning technique. Algorithm is scalable and outperforms algorithms like FP-Growth, in some cases even better. The performance improvements become more and more significant as the support threshold is decreased.

Key Words

Big Data; Incremental Mining; Frequent item-sets; Incremental data mining algorithm; Map-Reduce framework;

Cite This Article

"A Survey on an effective incremental mining algorithm for frequent item-sets with big data based on MapReduce framework ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 7, page no.1750-1756, July-2018, Available :http://www.jetir.org/papers/JETIRC006303.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A Survey on an effective incremental mining algorithm for frequent item-sets with big data based on MapReduce framework ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 7, page no. pp1750-1756, July-2018, Available at : http://www.jetir.org/papers/JETIRC006303.pdf

Publication Details

Published Paper ID: JETIRC006303
Registration ID: 184605
Published In: Volume 5 | Issue 7 | Year July-2018
DOI (Digital Object Identifier):
Page No: 1750-1756
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162


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