지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 저널정보
- 한국정보처리학회 JIPS(Journal of Information Processing Systems) JIPS(Journal of Information Processing Systems) 제17권 제4호
- 발행연도
- 2021.8
- 수록면
- 707 - 720 (14page)
- DOI
- 10.3745/JIPS.02.0159
이용수
초록· 키워드
오류제보하기
To improve the accuracy of the recommendation system, multi-criteria recommendation systems have beenwidely researched. However, it is highly complicated to extract the preferred features of users and items fromthe data. To this end, subjective indicators, which indicate a user’s priorities for personalized recommendations,should be derived. In this study, we propose a method for generating recommendation candidates by predictingmulti-criteria ratings from reviews and using them to derive user priorities. Using a deep learning model basedon convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), multi-criteriaprediction ratings were derived from reviews. These ratings were then aggregated to form a linear regressionmodel to predict the overall rating. This model not only predicts the overall rating but also uses the trainingweights from the layers of the model as the user’s priority. Based on this, a new score matrix forrecommendation is derived by calculating the similarity between the user and the item according to the criteria,and an item suitable for the user is proposed. The experiment was conducted by collecting the actual“TripAdvisor” dataset. For performance evaluation, the proposed method was compared with a generalrecommendation system based on singular value decomposition. The results of the experiments demonstratethe high performance of the proposed method.
목차
등록된 정보가 없습니다.
참고문헌 (9)
참고문헌 신청
Phonexay Vilakone / 2019 / Personalized Movie Recommendation System Combining Data Mining with the k-Clique Method / JIPS(Journal of Information Processing Systems) 15(5):1141~1155
송혜진 / 2019 / User Modeling Using User Preference and User Life Pattern Based on Personal Bio Data and SNS Data / JIPS(Journal of Information Processing Systems) 15(3):645~654
Z. Batmaz / 2019 / AE-MCCF : an autoencoder-based multi-criteria recommendation algorithm / Arabian Journal for Science and Engineering 44(11):9235~9247
M. Nilashi / 2014 / Hybrid recommendation approaches for multi-criteria collaborative filtering / Expert Systems with Applications 41(8):3879~3900
A. Ebadi / 2016 / A hybrid multi-criteria hotel recommender system using explicit and implicit feedbacks / International Journal of Computer and Information Engineering 10(8):1377~1385
송혜진 / 2019 / User Modeling Using User Preference and User Life Pattern Based on Personal Bio Data and SNS Data / JIPS(Journal of Information Processing Systems) 15(3):645~654
Z. Batmaz / 2019 / AE-MCCF : an autoencoder-based multi-criteria recommendation algorithm / Arabian Journal for Science and Engineering 44(11):9235~9247
M. Nilashi / 2014 / Hybrid recommendation approaches for multi-criteria collaborative filtering / Expert Systems with Applications 41(8):3879~3900
A. Ebadi / 2016 / A hybrid multi-criteria hotel recommender system using explicit and implicit feedbacks / International Journal of Computer and Information Engineering 10(8):1377~1385
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