Post ranking in a blogosphere

Won-Seok Hwang, Sang-Wook Kim
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Abstract

The existing post ranking algorithms overlook the category and the time interval, which are valuable information to improve the accuracy of algorithms. The category, created by a blogger, implies the interested topics of her/him, and the time interval between the generation of a post and a blog-action is related to the quality of post. This paper proposes two approaches that exploit the category and the time interval, and we apply our approaches to the existing post ranking algorithms, i.e. PostRank, BAITS, BloggerAVG. We evaluate the accuracy of these algorithms by conducting extensive experiments using real-world blog data, and the results show that our approaches help each algorithm improve the accuracy.
在博客圈中发布排名
现有的职位排名算法忽略了类别和时间间隔,这是提高算法准确性的重要信息。类别是由博主创建的,暗示着他/她感兴趣的话题,而文章产生和博客行动的时间间隔与文章的质量有关。本文提出了两种利用类别和时间间隔的方法,并将我们的方法应用于现有的帖子排名算法,即PostRank, BAITS, BloggerAVG。我们通过使用真实世界的博客数据进行广泛的实验来评估这些算法的准确性,结果表明我们的方法可以帮助每种算法提高准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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