Exploring Semantic Features for Producing Top-N Recommendation Lists from Binary User Feedback.
Nicholas AmpazisTheodoros EmmanouilidisPublished in: SemWebEval@ESWC (2014)
Keyphrases
- user feedback
- semantic features
- relevance feedback
- user interaction
- semantic information
- low level features
- visual features
- semantic similarity
- text classification
- wordnet
- document clustering
- user profiles
- user preferences
- recommender systems
- co occurrence
- learning to rank
- relevant documents
- feature set
- data mining
- language model
- support vector
- machine learning