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176267

Recommender System Approaches A Survey

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Last updated: 27 Dec 2024

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Abstract

Recommendation was mainly used within the online purchasing to propose list of products.  Recommender is depending on the information that filtered when seeking about the predicting of ‘score' of the user might provide to an item. Recommender systems are carried out in type of programs like movies, track, information, instructional occasions, venue, books, studies articles, and tourism, seek queries, social tags and merchandise in general.  Recommendation systems apply practice of data mining and prediction algorithms to expect person's hobby according to facts and most quantity of the merchandise he had. The paper offers outline recommender systems alongside the description of various strategies which might be being used for generating pointers. Recommendation strategies can be classified to a few classes: Collaborative Filtering, content material based totally and Hybrid guidelines, we've got discussed numerous strategies of recommender and techniques carried out to implement it. The intention of this work is to find out existing traits, open troubles and feasible directions for future studies.

DOI

10.21608/asc.2020.176267

Keywords

recommender system, Collaborative filtering, Content based filtering, Hybrid Recommender, Data mining

Volume

11

Article Issue

1

Related Issue

25529

Issue Date

2020-05-01

Receive Date

2021-05-08

Publish Date

2020-05-01

Page Start

30

Page End

38

Print ISSN

1687-8515

Online ISSN

2682-3578

Article File

ASC_Volume 11_Issue 1_Pages 30-38.pdf

PDF . 337.4kB

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https://asc.journals.ekb.eg/article_176267.html

Detail API

https://asc.journals.ekb.eg/service?article_code=176267

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Original Article

Type Code

1,549

Publication Type

Journal

Publication Title

Journal of the ACS Advances in Computer Science

Publication Link

https://asc.journals.ekb.eg/

MainTitle

Recommender System Approaches A Survey

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Type

Article

Created At

23 Jan 2023