While content-based recommendation has been applied successfully in many different domains, it has not seen the same level of attention as collaborative filtering techniques have. However, there are many recommendation domains and applications where content and metadata play a key role, either in addition to or instead of ratings and implicit usage data. For some domains, such as movies, the relationship between content and usage data has seen thorough investigation already, but for many other domains, such as books, news, scientific articles, and Web pages we still do not know if and how these data sources should be combined to provided the best recommendation performance. The CBRecSys 2015 workshop aims to address this by providing a dedicated venue for papers dedicated to all aspects of content-based recommendation.
|Series||CEUR Workshop Proceedings|
|Period||16/09/2015 → 20/09/2015|
- recommender systems
- content-based recommendation
- text reviews
- user-generated content
- implicit feedback