Preliminary Investigation of Alleviating User Cold-Start Problem in E-commerce with Deep Cross-Domain Recommender System.
Hanxin WangDaichi AmagataTakuya MaekawaTakahiro HaraHao NiuKei YonekawaMori KurokawaPublished in: WWW (Companion Volume) (2019)
Keyphrases
- cold start problem
- recommender systems
- cross domain
- preliminary investigation
- collaborative filtering
- cold start
- data sparsity
- transfer learning
- matrix factorization
- product recommendation
- personalized recommendation
- user interests
- user preferences
- implicit feedback
- knowledge transfer
- sentiment classification
- user feedback
- user profiles
- text categorization
- recommendation algorithms
- information overload
- user model
- data sparseness
- user interface
- data mining
- tag recommendation
- active learning
- high dimensional
- natural language
- machine learning