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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM11841

A Hybrid Approach of Collaborative Filtering and Genetic Algorithm for Product Recommendation System

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM11841

Volume:

6 |

3 |

Mar 2022

Pages:

Publication Frequency:

Monthly (12 issues per year)

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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

SPD

Shalaka Prasad Deore

TJ

Tejashree Jagtap

AB

Amruta Bendale

RP

Rutuja Pawar

RV

Ritika Valesha

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Abstract

Data mining is an critical research space in recent times that focuses on the supply of facts in records. this is in which records from the internet site is mined so that informative facts can be processed and used correctly and correctly through people. Its cause is to expect and interpret. one of the functions of data mining is the association Rule mine. It consists of two procedures: First, locating the frequently used objects on the web site the usage of a little assist and developing a rule of relation to commonplace items with a unique confidence. it is related to the affiliation of items wherein in all A-occasions, there may be a B-occurrence. This mine could be very effective in reading the marketplace basket. That app is useful for clients who purchase positive gadgets. that during the entirety they bought, it can be something / matters that could be mixed with some thing offered. MLP and genetic algorithm are the most widely used association mining association set of rules.

KEYWORDS

Genetic set of rules collaborative filtering recommendation application

Cite This Article

Shalaka Prasad Deore, Tejashree Jagtap, Amruta Bendale, Rutuja Pawar, Ritika Valesha, "A Hybrid Approach of Collaborative Filtering and Genetic Algorithm for Product Recommendation System," International Journal of Scientific Research in Engineering and Management, vol. 6, no. 3, Mar 2022.

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Publication Date

3/14/2022

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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5

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The authors declare no conflict of interest related to this research work.

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