Collaborative filtering is one of the commonly used methods in the web recommendation system. Numerous researches on the collaborative filtering proposed the numbers of measures for enhancing the accuracy. This study suggests the movie recommendation system applied with Word2Vec and ensemble convolutional neural networks. First, user sentences and movie sentences are made from the user, movie, and rating information. Then, the user sentences and movie sentences are input into Word2Vec to figure out the user vector and movie vector. The user vector is input on the user convolutional model while the movie vector is input on the movie convolutional model. These user and movie convolutional models are connected to the fully-connected neural network model. Ultimately, the output layer of the fully-connected neural network model outputs the forecasts for user, movie, and rating. The test result showed that the system proposed in this study showed higher accuracy than the conventional cooperative filtering system and Word2Vec and deep neural network-based system suggested in the similar researches. The Word2Vec and deep neural network-based recommendation system is expected to help in enhancing the satisfaction while considering about the characteristics of users.
조선대학교 기초과학연구원 [The Natural Science Research Institute of Chosun]
설립연도
2008
분야
자연과학>자연과학일반
소개
본 연구원은 기초과학을 진흥하기 위한 연구·교육 및 그 보급을 목적으로 한다. 이 목적을 달성하기 위하여 다음 각 호의 사업을 수행한다.
1. 기초과학 제 분야에 관한 조사와 연구
2. 기초과학에 관한 학술행사(학술대회, 학술세미나, 심포지엄, 초청강연회 등) 개최
3. 학문후속세대 및 일반인을 위한 기초과학 교육
4. 기관지『조선자연과학논문지』 발간
5. 『자연과학연구총서』, 『자연과학번역총서』 등 단행본 발간
6. 기타 본 연구원의 목적과 관련된 사업
간행물
간행물명
통합자연과학논문집(구 조선자연과학논문집) [Journal of Integrative Natural Science]