Multicriteria Movie Recommendation Model Combining Aspect-based Sentiment Classification Using BERT (BERT 기반의 속성기반 감성분석을 활용한 다기준 영화 추천 모형)

Yurin Lee (이유린); Ahn, Hyunchul (안현철)

doi:10.9708/jksci.2022.27.03.201

Multicriteria Movie Recommendation Model Combining Aspect-based Sentiment Classification Using BERT

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2022, 27(3), pp.201-207
DOI : 10.9708/jksci.2022.27.03.201
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : February 21, 2022
Accepted : March 23, 2022
Published : March 31, 2022

Yurin Lee ¹, Ahn, Hyunchul ¹

¹국민대학교

Accredited

ABSTRACT

In this paper, we propose a movie recommendation model that uses the users’ ratings as well as their reviews. To understand the user’s preference from multicriteria perspectives, the proposed model is designed to apply attribute-based sentiment analysis to the reviews. For doing this, it divides the reviews left by customers into multicriteria components according to its implicit attributes, and applies BERT-based sentiment analysis to each of them. After that, our model selectively combines the attributes that each user considers important to CF to generate recommendation results. To validate usefulness of the proposed model, we applied it to the real-world movie recommendation case. Experimental results showed that the accuracy of the proposed model was improved compared to the traditional CF. This study has academic and practical significance since it presents a new approach to select and use models in consideration of individual characteristics, and to derive various attributes from a review instead of evaluating each of them.

KEYWORDS

Recommender Systems, Collaborative Filtering, Multicriteria Recommendation, Aspect-Based Sentiment Analysis, BERT

Citation status

* References for papers published after 2023 are currently being built.

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[web] / https://github.com/huggingface/pytorch-pretrained-BERT / https://github.com/huggingface/pytorch-pretrained-BERT

[web] / https://movie.daum.net/main / https://movie.daum.net/main

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This paper was written with support from the National Research Foundation of Korea.

KJCKorea
Journal Central

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Multicriteria Movie Recommendation Model Combining Aspect-based Sentiment Classification Using BERT

ABSTRACT

KEYWORDS

Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

Multicriteria Movie Recommendation Model Combining Aspect-based Sentiment Classification Using BERT

ABSTRACT

KEYWORDS

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REFERENCES (22) * References for papers published after 2023 are currently being built.

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* References for papers published after 2023 are currently being built.