VAST '07 Proceedings of the 2007 IEEE Symposium on Visual Analytics Science and Technology
An online video recommendation framework using rich information
Proceedings of the Third International Conference on Internet Multimedia Computing and Service
Integrating rich information for video recommendation with multi-task rank aggregation
MM '11 Proceedings of the 19th ACM international conference on Multimedia
A unified framework for web video topic discovery and visualization
Pattern Recognition Letters
Hi-index | 0.00 |
In this paper, we have developed an interactive system to enable personalized news video recommendation. First, multi-modal information channels (audio, video and closed captions) are seamlessly integrated and synchronized to achieve more reliable news topic detection, and the contextual relationships between the news topics are extracted automatically. Second, topic network and hyperbolic visualization are seamlessly integrated to achieve interactive navigation and exploration of large-scale collections of news videos at the topic level, so that users can have a good global overview of large-scale collections of news videos at the first glance. In such interactive topic network navigation and exploration process, the users' personal background knowledge can be taken into consideration for obtaining the news topics of interest interactively, building up their mental models of news needs precisely and formulating their searches easily by selecting the visible news topics on the screen directly. Our system can further recommend the relevant web news, the new search directions, and the most relevant news videos according to their importance and representativeness scores.