基于社交活动的用户生成视频内容排序算法

Lisa Wiyartanti, Yo-Sub Han, Laehyun Kim
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引用次数: 6

摘要

人们每天上传极其大量的用户生成内容,并参与与网络内容相关的各种社会活动。因此,研究人员开发了高效的用户生成内容管理系统。典型的社交活动是添加喜爱列表、给出评级、订阅和给出评论。我们观察到,我们可以使用这些活动来评估内容的价值。在此基础上,我们引入了一种用户生成视频内容的排序算法。该算法利用社会活动中的集体智慧,发现有影响力的用户,计算内容价值,并通过统计方法对内容进行排序。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A ranking algorithm for user-generated video contents based on social activities
People upload extremely large number of user-generated contents everyday and participate in various social activities regarding with contents on the Web. Thus, researchers develop efficient user-generated content management systems. Typical social activities are to add favorite list, give rating, subscribe, and give comments. We observe that we can use these activities for evaluating the value of contents. Based on this observation, we introduce a ranking algorithm for user-generated video contents. We make use of collective intelligence from social activities and the algorithm finds influential users, calculates the value of contents, and orders the contents by statistical method.
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