A content based and collaborative filtering recommender system

Vignesh Thannimalai; Li Zhang

doi:10.1109/ICMLC54886.2021.9737238

A content based and collaborative filtering recommender system

Vignesh Thannimalai, Li Zhang

Computer and Information Sciences Department

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

8 Citations (Scopus)

Abstract

This research proposes a new recommendation system for recommendation generation based on users' ratings and personal profiles. Motivated by existing studies, firstly we propose item-based collaborative filtering to recommend tourist spots based on users' rating. In addition, we incorporate the content-based filtering algorithm with Naïve Bayes Classifier, for recommendation generation. Detailed analysis of these proposed methods are discussed which will give a clear view on how the core part of the recommendation systems has been implemented. The proposed TRS was evaluated using several data sets to indicate its efficiency.

Original language	English
Title of host publication	Proceedings of 2021 International Conference on Machine Learning and Cybernetics, ICMLC 2021
Publisher	IEEE
ISBN (Electronic)	9781665466080
DOIs	https://doi.org/10.1109/ICMLC54886.2021.9737238
Publication status	Published - 2021
Event	20th International Conference on Machine Learning and Cybernetics, ICMLC 2021 - Adelaide, United States Duration: 4 Dec 2021 → 5 Dec 2021

Publication series

Name	Proceedings - International Conference on Machine Learning and Cybernetics
Volume	2021-December
ISSN (Print)	2160-133X
ISSN (Electronic)	2160-1348

Conference

Conference	20th International Conference on Machine Learning and Cybernetics, ICMLC 2021
Country/Territory	United States
City	Adelaide
Period	4/12/21 → 5/12/21

Keywords

Collaborative filtering
Content-based filtering
Naïve Bayes classifier
Ratings and personalized profile
Recommendation system

Access to Document

10.1109/ICMLC54886.2021.9737238

Cite this

@inproceedings{e4106313401b420ab24bf2b5f6dc61cb,

title = "A content based and collaborative filtering recommender system",

abstract = "This research proposes a new recommendation system for recommendation generation based on users' ratings and personal profiles. Motivated by existing studies, firstly we propose item-based collaborative filtering to recommend tourist spots based on users' rating. In addition, we incorporate the content-based filtering algorithm with Na{\"i}ve Bayes Classifier, for recommendation generation. Detailed analysis of these proposed methods are discussed which will give a clear view on how the core part of the recommendation systems has been implemented. The proposed TRS was evaluated using several data sets to indicate its efficiency. ",

keywords = "Collaborative filtering, Content-based filtering, Na{\"i}ve Bayes classifier, Ratings and personalized profile, Recommendation system",

author = "Vignesh Thannimalai and Li Zhang",

note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 20th International Conference on Machine Learning and Cybernetics, ICMLC 2021 ; Conference date: 04-12-2021 Through 05-12-2021",

year = "2021",

doi = "10.1109/ICMLC54886.2021.9737238",

language = "English",

series = "Proceedings - International Conference on Machine Learning and Cybernetics",

publisher = "IEEE",

booktitle = "Proceedings of 2021 International Conference on Machine Learning and Cybernetics, ICMLC 2021",

address = "United States",

}

Thannimalai, V & Zhang, L 2021, A content based and collaborative filtering recommender system. in Proceedings of 2021 International Conference on Machine Learning and Cybernetics, ICMLC 2021. Proceedings - International Conference on Machine Learning and Cybernetics, vol. 2021-December, IEEE, 20th International Conference on Machine Learning and Cybernetics, ICMLC 2021, Adelaide, United States, 4/12/21. https://doi.org/10.1109/ICMLC54886.2021.9737238

A content based and collaborative filtering recommender system. / Thannimalai, Vignesh; Zhang, Li.
Proceedings of 2021 International Conference on Machine Learning and Cybernetics, ICMLC 2021. IEEE, 2021. (Proceedings - International Conference on Machine Learning and Cybernetics; Vol. 2021-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Thannimalai, Vignesh

AU - Zhang, Li

PY - 2021

Y1 - 2021

N2 - This research proposes a new recommendation system for recommendation generation based on users' ratings and personal profiles. Motivated by existing studies, firstly we propose item-based collaborative filtering to recommend tourist spots based on users' rating. In addition, we incorporate the content-based filtering algorithm with Naïve Bayes Classifier, for recommendation generation. Detailed analysis of these proposed methods are discussed which will give a clear view on how the core part of the recommendation systems has been implemented. The proposed TRS was evaluated using several data sets to indicate its efficiency.

AB - This research proposes a new recommendation system for recommendation generation based on users' ratings and personal profiles. Motivated by existing studies, firstly we propose item-based collaborative filtering to recommend tourist spots based on users' rating. In addition, we incorporate the content-based filtering algorithm with Naïve Bayes Classifier, for recommendation generation. Detailed analysis of these proposed methods are discussed which will give a clear view on how the core part of the recommendation systems has been implemented. The proposed TRS was evaluated using several data sets to indicate its efficiency.

KW - Collaborative filtering

KW - Content-based filtering

KW - Naïve Bayes classifier

KW - Ratings and personalized profile

KW - Recommendation system

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U2 - 10.1109/ICMLC54886.2021.9737238

DO - 10.1109/ICMLC54886.2021.9737238

M3 - Conference contribution

AN - SCOPUS:85127821260

T3 - Proceedings - International Conference on Machine Learning and Cybernetics

BT - Proceedings of 2021 International Conference on Machine Learning and Cybernetics, ICMLC 2021

PB - IEEE

T2 - 20th International Conference on Machine Learning and Cybernetics, ICMLC 2021

Y2 - 4 December 2021 through 5 December 2021

ER -

A content based and collaborative filtering recommender system

Abstract

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Keywords

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