Personalized Content RecommendationsMay 10, 2013
- How to detect user interests and automatically recommend interesting contents in a personalized way.
- Detecting user interests through attention time, i.e. time spent by a user on reading a certain webpage.
- Collaboratively mining semantic contents of user reading materials along with one’s implicit feedbacks.
- Advanced data fusion algorithms for user interest inference.
- Dynamic content recommendations according to inferred user interest profile.
Advantage over the State-of-the-Art
- Leverage an ontology based approach for noise tolerant user interest inference.
- Can autonomously recommend interesting contents to end users without explicit user participation.
- Capable of detecting dynamic user interest shift fully automatically and adjust algorithm behaviors accordingly.
Prototype website: http://www.smartdataware.com