【摘要】 针对现有推荐系统电影评分不实、影响推荐精确度的问题,本文设计了一个基于电影影评的电影推荐系统。本系统首先利用网络爬虫技术获取电影影评,然后对抓取到的数据进行分析和预处理,挖掘出电影影评中的关键词并进行正负词性的分类,然后计算出影评的好评率,根据好评率进行电影推荐,可以使得推荐结果更符合用户的偏好和需求。实验结果表明,利用影评好评率进行推荐大大提高了电影推荐的精确度,可以有效保证电影推荐系统的推荐质量。更多还原

【Abstract】 Aiming at the problem that the existing recommendation system film is not true and affects the accuracy of recommendation this paper designs a film recommendation system based on movie film review. The system first uses the web crawler technology to obtain movie review then analyzes and preprocesses the captured data mines the keywords in the movie review and classifies the positive and negative words and then calculates the favorable rate of the film review. The rate of film recommendation can make the recommendation result more in line with the user’s preferences and needs. The experimental results show that the recommendation by using the favorable rating of the film evaluation greatly improves the accuracy of the film recommendation and can effectively guarantee the recommendation quality of the movie recommendation system.更多还原