Audience Behavior Mining: Integrating TV Ratings with Multimedia Content

TV ratings play an important role in the analysis of advertising, risk management, and social trends. The ratings reflect the interests of audiences, so valuable knowledge could be discovered by analyzing ratings in combination with multimedia content, such as broadcast video and transcripts. This article establishes a general framework for mining audience behaviors. The authors focus on change points in TV ratings data, which reflect the active intentions of users. Meaningful patterns are extracted from a large number of change points by filtering and aggregating the data. The authors propose two applications based on their framework--interactive audience behavior mining tools and popular news topic detection. The results demonstrate that their framework can extract valuable knowledge from TV ratings data.