Hierarchical content group detection from different social media platforms using Web link structure
Hierarchical content group detection from different social media platforms using Web link structure
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DOI：
10.1109/icip.2016.7532403
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发表时间：
2016-08
期刊：
影响因子：
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通讯作者：
Daichi Takehara;Ryosuke Harakawa;Takahiro Ogawa;M. Haseyama
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文献类型：
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作者：
Daichi Takehara;Ryosuke Harakawa;Takahiro Ogawa;M. Haseyama
本文提出了一种从不同的社交媒体平台，它可以揭示内容组的层次结构的分层内容组检测方法。在本文中，内容组被定义为具有相似主题的内容集合。基于所揭示的层次结构，我们的方法使用户能够有效地找到所需的内容，从大量的内容放置在多样化的社交媒体平台。本文的主要贡献是双重的。首先，通过结合使用从不同社交媒体平台获得的特征之间的相关性和Web链接结构，可以提取用于比较放置在不同社交媒体平台上的内容的有效潜在特征。第二，内容组的层次结构，它捕捉他们的各种抽象级别，可以通过分层检测他们的内容组揭示。在包含YouTube视频和Wikipedia文章的真实数据集上的实验结果表明了该方法的有效性。
This paper presents a method for hierarchical content group detection from different social media platforms, which can reveal hierarchical structure of content groups. In this paper, content groups are defined as sets of contents with similar topics. Based on the revealed hierarchical structure, our method enables users to efficiently find the desired contents from large amount of contents placed in diversified social media platforms. The main contributions of this paper are twofold. First, effective latent features for comparing the contents placed in different social media platforms can be extracted by the combination use of the correlation between features obtained from different social media platform and the Web link structure. Second, the hierarchical structure of the content groups, which captures their various abstraction levels, can be revealed by hierarchically detecting their content groups. Experimental results on the real-world dataset containing YouTube videos and Wikipedia articles show the effectiveness of our method.