Utilize Item Correlation to Improve Aggregate Diversity for Recommender Systems.
Yezheng LiuJinkun WangYuanchun JiangJianshan SunChunhua SunPublished in: DSC (2016)
Keyphrases
- recommender systems
- collaborative filtering
- cold start problem
- item based collaborative filtering
- artificial intelligence
- user modeling
- matrix factorization
- user preferences
- prediction accuracy
- user profiles
- item recommendation
- personalized recommendation
- recommendation algorithms
- data sets
- multi objective
- user interface
- decision trees
- clustering algorithm
- website
- machine learning