UGC Approved Journal no 63975(19)

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

Volume 6 Issue 3
March-2019
eISSN: 2349-5162

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

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Published Paper ID:
JETIRAU06004


Registration ID:
202316

Page Number

19-25

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Title

.AN EFFECTIVE COLLABORATIVE FILTERING FOR UNPREFERED ITEMS BY USING L- INJECTION

Abstract

In recent years there has been a dramatic increase in the amount of online content. Recommender systems form a specific type of Information Filtering (IF) technique. To date a number of recommendation algorithms have been proposed, where collaborative filtering is one of the most famous and adopted recommendation technique. Collaborative filtering recommender systems recommend items by identifying other users with similar taste and use their opinions for recommendation. In the last decade, the amount of customers and online information has grown rapidly, yielding the big data analysis problem for recommender systems. Consequently, traditional recommender systems often suffer from scalability and inefficiency problems when processing or analysing such large-scale data. Due to this, the implementation of these algorithms on single node machine is time consuming and fail to meet the computing requirement of large data sets. Distributed processing of big data across multiple clusters of nodes can help to improve the performance in such cases. In this paper, the former collaborative filtering recommendation algorithm is designed to parallel on MapReduce framework and uses Pearson correlation as similarity metric. Apache Hadoop is parallel distributed framework. Hadoop distributed file system(HDFS) allows distributed processing of big data across multiple clusters of nodes.

Key Words

Recommendation, Collaborative filtering, Pearson correlation, Apache Mahout, Hadoop

Cite This Article

".AN EFFECTIVE COLLABORATIVE FILTERING FOR UNPREFERED ITEMS BY USING L- INJECTION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.19-25, March-2019, Available :http://www.jetir.org/papers/JETIRAU06004.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

".AN EFFECTIVE COLLABORATIVE FILTERING FOR UNPREFERED ITEMS BY USING L- INJECTION ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp19-25, March-2019, Available at : http://www.jetir.org/papers/JETIRAU06004.pdf

Publication Details

Published Paper ID: JETIRAU06004
Registration ID: 202316
Published In: Volume 6 | Issue 3 | Year March-2019
DOI (Digital Object Identifier):
Page No: 19-25
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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