Eunice Tan, I. Seaman, Humphrey C. H. Leung, Yiu-Kai Ng
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引用次数: 7
摘要
多媒体对儿童的社会和心理发展有重大影响,因为儿童经常接触不适当的材料,包括可以在网上或通过其他多媒体渠道获得的电影。虽然不是所有的电影都是坏的,但电影中表现出的攻击性语言、暴力和性行为也会产生负面影响。父母和孩子的指导需要所有他们能得到的帮助来促进电影的健康使用。为了向他们提供适合他们的青少年的电影,我们开发了MovReC,这是一个个性化的儿童电影推荐,旨在为儿童提供教育和合适的娱乐机会。与亚马逊和其他在线电影推荐系统(如Common Sense Media, IMDb和TasteKid)不同,MovReC是独一无二的,因为据我们所知,MovReC是第一个个性化的儿童电影推荐系统。此外,MovReC根据使用反向传播模型计算的适合儿童的分数,使用LDA预定义的类别,使用矩阵分解的预测评分,以及基于用户评论的情绪来确定电影对特定用户的吸引力,以及它的喜欢/不喜欢计数和类型,产生MovReC考虑的特征。MovReC通过使用CombMNZ模型将这些特征结合起来,对电影进行排名和推荐。MovReC的性能评估清楚地表明了它的有效性,它推荐的电影受到了用户的高度评价。
Making personalized movie recommendations for children
Multimedia have significant impact on the social and psychological development of children who are often explored to inappropriate materials, including movies that are either accessible online or through other multimedia channels. Even though not all movies are bad, there are negative effects of offensive languages, violence, and sexuality as exhibited in movies. Parents and guidance of children need all the help they can get to promote the healthy use of movies these days. To offer them appropriate movies of interest to their youths, we have developed MovReC, a personalized movie recommender for children, which is designed to provide educational and suitable entertaining opportunities for children. Unlike Amazon and other online movie recommendation systems, such as Common Sense Media, IMDb, and TasteKid, MovReC is unique, since to the best of our knowledge MovReC is the first personalized children movie recommender. Moreover, MovReC determines the appealingness of a movie for a particular user based on its children-appropriate score computed by using the Backpropagation model, pre-defined category using LDA, its predicted rating using Matrix Factorization, and sentiments based on its users' reviews, which along with its like/dislike count and genres, yield the features considered by MovReC. MovReC combines these features by using the CombMNZ model to rank and recommend movies. The performance evaluation of MovReC clearly demonstrates its effectiveness and its recommended movies are highly regarded by its users.