Real-Time LDCRF-Based Method for Inferring TV Viewer Interest

Context-awareness provides users with more versatile user interface environments when using digital devices. In a TV viewing environment, context-awareness techniques can be used for recommending useful information related to the viewed program. To incorporate a user´s preference in doing so, it is vital to infer whether the viewer is actually interested in the TV program. Therefore, we propose a method for inferring viewer interest in a TV program. In the proposed method, we regard the problem of inferring viewer interest as a sequential labeling problem and solve it by applying latent dynamic conditional random fields to data sequences generated by integrating the operational log information of user interaction and visual information of viewer behaviors.