Movie Recommender system using Sentiment Analysis

Anmol Chauhan, Deepank Nagar, Prashant Chaudhary
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Abstract

In Todays era, Recommendation systems are the most important intelligent systems that plays in giving the information to the users. Previously approaches in recommendation systems (RS) include Content-based-filtering and collaborative filtering. Thus, these approaches has certain limitations as like the necessity of the user history as they visit. So as to make back the effect of such dependencies, this research paper provides a hybrid RS are those which mixes both Collaborative filtering, Content based filtering with sentiment analysis of movies. In this research paper, we developed a recommender system based on the sentiment of the user to suggest the movie to the user based on their view history.
使用情感分析的电影推荐系统
在当今时代,推荐系统是向用户提供信息的最重要的智能系统。推荐系统中已有的方法包括基于内容的过滤和协同过滤。因此,这些方法有一定的局限性,比如在用户访问时需要用户历史记录。为了抵消这种依赖的影响,本文提出了一种混合了协同过滤、基于内容的过滤和电影情感分析的混合RS。在本文中,我们开发了一个基于用户情感的推荐系统,根据用户的观看历史向用户推荐电影。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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