A paper entitled 'Public Interest Analysis Based on Implicit Feedback of IPTV Users' has been published recently in IEEE Transactions on Industrial Informatics. This paper is a joint work with colleagues of University of Ljubljana, Slovenia, and Dr Yuan Zhang is the corresponding author. This paper can be accessedhere.
Abstract: Modern information systems make it increasingly easy to gain more insight into the public interest, which is becoming more and more important in diverse public and corporate activities and processes. The disadvantage of existing research that focuses on mining the information from social networks and online communities is that it does not uniformly represent all population groups and that the content can be subjected to self-censoring or curation. In this paper, we propose and describe a framework and a method for estimating public interest from the implicit negative feedback collected from the Internet protocol television (IPTV) audience. Our research focuses primarily on the channel change events and their match with the content information obtained from closed captions. The presented framework is based on concept modeling, viewership profiling, and combines the implicit viewer reactions (channel changes) into an interest score. The proposed framework addresses both above-mentioned disadvantages or concerns. It is able to cover a much broader population, and it can detect even minor variations in user behavior. We demonstrate our approach on a large pseudonymized real-world IPTV dataset provided by an ISP, and show how the results correlate with different trending topics and with parallel classical long-term population surveys.
最近，USLab与斯洛文尼亚University of Ljubljana的4位同行合作，在期刊IEEE Transactions on Industrial Informatics发表了论文“Public Interest Analysis Based on Implicit Feedback of IPTV Users”。张远博士是该论文通讯作者，论文提出了利用潜式IPTV观众信息（负面的反馈）来评估公众兴趣的框架和方法，全文可以在此处获取。