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中文摘要：
利用新浪微博的微群信息,在蚁群算法的基础上,提出了一种基于群体智慧思想的排序模型（ACOR）,通过结合用户的偏好及电影热度对电影进行综合排名.同时考虑了微博中的情感因素,分析用户对电影的情感倾向并计算其情感值.最后,根据群体形成的情感积累值对热议的电影排序.实验结果表明：该模型更符合用户的偏好,并具有一定的实时性,可以有效地为用户提供相关电影信息.
英文摘要：
A ranking model based on the collective intelligence and which exploited the Ant Colony Algorithm to make the rank on the information of micro-group in the Sina Weibo has been proposed.At the same time,by combining with the extent of user＇s preference and the hot extent of movies,a comprehensive ranking is given.Besides,the emotion factor of micro-blogging is considered to analysis the users＇ emotion tendency and the value of the emotion is computed.The final ranking is based on the accumulative value of emotion about the hot movies in the group.The experiment shows that this model can meet the users＇ preference better than other method.And it has some degree of real-time properties to provide users with relevant information of movies effectively.
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Incorporating rich features to boost information retrieval performance: A SVM-regression based re-ra
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