- Publication Details
- TRECVID Workshop
- Mar March 1, 2017
We are building video recommendation systems that explore two directions of inquiry. First, for domains such as educational video (i.e. videos from massive open online courses) we explore how to build recommendation systems that model both the prominent topical structure of the content, and also account for the sequential nature of inter-topic relationships. Second, we explore how to use automatic understanding of the content’s topics to better contextualize recommendations provided to users, and also to improve their navigation experience within large content collections.
This project also includes participation in the TRECVID video hyperlinking benchmark in which we have successfully validated our content processing pipelines.