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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: April 2024

Volume 9 | Issue 4

Impact factor: 8.15

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Paper Title: A NOVEL TRANSACTION REDUCTION & DATA ELIMINATION BASED TECHNIQUE FOR MINING FREQUENT ITEM SETS FROM A TRANSACTION DATA BASE
Authors Name: Rupesh Panwar , Prof. Abhishek Raghuvanshi
Unique Id: IJSDR1604061
Published In: Volume 1 Issue 4, April-2016
Abstract: Data mining automates the process of finding predictive information in large databases. Questions that traditionally required extensive hands-on analysis can now be answered directly from the data — quickly. A typical example of a predictive problem is targeted marketing. In this paper, we have developed a method to discover large item sets from the transaction database. The proposed methodology uses an elimination based technique for frequent item set mining. The proposed method reduces the transaction which does not contain any frequent item in the initial steps of the frequent item set mining process. The proposed method eliminates the infrequent item sets from the transaction data base to convert it in to a reduced transaction data base. The proposed method is fast in comparison to older algorithms. Also it takes les main memory space for computation purpose. Experimental results have proved that the proposed scheme is time and memory efficient.
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Cite Article: "A NOVEL TRANSACTION REDUCTION & DATA ELIMINATION BASED TECHNIQUE FOR MINING FREQUENT ITEM SETS FROM A TRANSACTION DATA BASE", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.1, Issue 4, page no.344 - 346, April-2016, Available :http://www.ijsdr.org/papers/IJSDR1604061.pdf
Downloads: 000337067
Publication Details: Published Paper ID: IJSDR1604061
Registration ID:160224
Published In: Volume 1 Issue 4, April-2016
DOI (Digital Object Identifier):
Page No: 344 - 346
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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