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Learning Automata Based Sentiment Analysis for recommender system on cloud

机译:基于机构的云推荐系统学习自动数据的情感分析

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The development of personalized recommendation systems has been an interesting research topic after the rapid evolution in social networking sites. In this paper, we propose a recommendation system using Learning automata (LA) and sentiment analysis. LA is used to optimize the recommendation score produced by the proposed system using sentiment analysis. The proposed Learning Automata-Based Sentiment Analysis System (LASA) recommends the places nearby the current location of the users by analyzing the feedback from the places and thus calculating the score based on it. Experiments performed by us indicate that by using LA, we can improve the performance of the proposed system, and, thus, help a user to find a specific location according to the need.
机译:社交网站快速演变后,个性化推荐系统的发展是一个有趣的研究主题。在本文中,我们提出了一种推荐系统,使用学习自动机(LA)和情感分析。 LA用于优化所提出的系统产生的推荐分数,使用情感分析。基于学习的基于自动数据的情绪分析系统(LASA)推荐了用户通过分析来自地点的反馈并根据其计算得分来推荐用户当前位置附近的地点。由我们执行的实验表明,通过使用LA,我们可以提高所提出的系统的性能,从而帮助用户根据需要找到特定位置。

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