一种基于AHP的智能电影推荐方法
Intelligent movie recommendation method based on AHP

电影网站提供了十分丰富的电影资源，然而用户必须花费大量时间搜索自己感兴趣的资源，如何帮助用户快速找到其想要的资源成为大型电影网站的重要需求。智能推荐技术的提出使满足这个需求成为可能。文中提出一种基于AHP（Analytic Hierarchy Process）层次分析法的智能电影推荐方法，综合考虑电影印象、故事、表演、导演、画面、音乐和类型等因素，通过用户对各因素两两比较、权重计算，生成个性化推荐列表。基于时光网的多个用户实证研究表明，结合AHP的智能电影推荐方法简单、有效，大部分推荐结果满足用户喜好。
Film websites can provide abundant movie resources. However, users must spend a lot of time to search for contens they are interested in. How to find what users like is an important requirement in large film website searching. Intelligent recommendation technologies make satisfying the requirement possible. This paper proposes an intelligent movie recommendation method based on analytic hierarchy process (AHP). By pairwise comparison of factors, such as the impression, plot, performance, director, frame, music and type of movie, and weight computation, the personalized recommendation list is produced. Multiple case studies of users based on website of mtime show that the movie recommendation method with AHP is simple, effective,thus most recommendation results can satisfy users’ tastes