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首页> 外文期刊>ACM transactions on multimedia computing communications and applications >Exploiting Content Relevance and Social Relevance for Personalized Ad Recommendation on Internet TV
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Exploiting Content Relevance and Social Relevance for Personalized Ad Recommendation on Internet TV

机译：利用内容相关性和社会相关性在互联网电视上推荐个性化广告

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摘要

There have been not many interactions between the two dominant forms of mass communication: television and the Internet, while nowadays the appearance of Internet television makes them more closely. Different with traditional TV in a passive mode of transmission, Internet TV makes it more possible to make personalized service recommendation because of the interactivity between users and the Internet. In this article, we introduce a scheme to provide targeted ad recommendation to Internet TV users by exploiting the content relevance and social relevance. First, we annotate TV videos in terms of visual content analysis and textual analysis by aligning visual and textual information. Second, with user-user, video-video and user-video relationships, we employ Multi-Relationship based Probabilistic Matrix Factorization (MRPMF) to learn representative tags for modeling user preference. And then semantic content relevance (between product/ad and TV video) and social relevance (between product/ad and user interest) are calculated by projecting the corresponding tags into our advertising concept space. Finally, with relevancy scores we make ranking for relevant product/ads to effectively provide users personalized recommendation. The experimental results demonstrate attractiveness and effectiveness of our proposed approach.
机译：电视和互联网这两种主要的大众传播形式之间没有太多的互动，而如今互联网电视的出现使它们之间的联系更加紧密。与传统电视的被动传输方式不同，由于用户与互联网之间的交互作用，互联网电视使个性化服务推荐成为可能。在本文中，我们介绍了一种通过利用内容相关性和社会相关性向互联网电视用户提供定向广告推荐的方案。首先，我们通过对齐视觉和文字信息，在视觉内容分析和文字分析方面对电视视频进行注释。其次，通过用户-用户，视频-视频和用户-视频之间的关系，我们采用基于多关系的概率矩阵分解（MRPMF）来学习用于建模用户偏好的代表性标签。然后，通过将相应的标签投影到我们的广告概念空间中，来计算语义内容相关性（产品/广告与电视视频之间）和社交相关性（产品/广告与用户兴趣之间）。最后，通过相关性得分，我们对相关产品/广告进行排名，以有效地向用户提供个性化推荐。实验结果证明了我们提出的方法的吸引力和有效性。

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