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Conversational Recommendation System based on Sentiment Analysis
LI Xinsheng,LI Jian *
Beijing University of Posts and Telecommunications, Beijing, 100876
*Correspondence author
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Funding: none
Opened online: 3 March 2020
Accepted by: none
Citation: LI Xinsheng,LI Jian.Conversational Recommendation System based on Sentiment Analysis[OL]. [ 3 March 2020] http://en.paper.edu.cn/en_releasepaper/content/4750892
 
 
The combination of the recommender system and dialogue system which called the conversational recommendation system is a growing interest. Tosolve the problem that it is difficult to obtain users' tastes in conversational recommendation systems. A sentiment analysis method is proposed in our conversational recommendation model to get user preferences. A sentiment analysis dataset is created and the model uses a sentiment analysis approach to obtain a movie seeker\'s preferences and make a recommendation. Experimentresults show that our sentiment analysis model yields a better performance of 0.8362(F1 score) than the baseline(0.7802) and other models. Thus, the movie recommended by our system can meet the needs of users better.
Keywords:Artificial Intelligence, Dialogue System; Recommender System; Sentiment Analysis
 
 
 

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