Collaborative information and semantic information Fusion over Heterogeneous information Network for Top-N Recommendation System
Abstract
References
Index Terms
- Collaborative information and semantic information Fusion over Heterogeneous information Network for Top-N Recommendation System
Recommendations
Personalized Recommendation Algorithm Using User Demography Information
WKDD '09: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data MiningPersonalized recommendation systems are web-based systems that aim at predicting a user’s interest on available products and services by relying on previously rated items and dealing with the problem of information and product overload. User demography ...
A Hybrid Multigroup Coclustering Recommendation Framework Based on Information Fusion
Special Section on Visual Understanding with RGB-D SensorsCollaborative Filtering (CF) is one of the most successful algorithms in recommender systems. However, it suffers from data sparsity and scalability problems. Although many clustering techniques have been incorporated to alleviate these two problems, ...
Local and Global Information Fusion for Top-N Recommendation in Heterogeneous Information Network
CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge ManagementSince heterogeneous information network (HIN) is able to integrate complex information and contain rich semantics, there is a surge of HIN based recommendation in recent years. Although existing methods have achieved performance improvement to some ...
Comments
Information & Contributors
Information
Published In

Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Check for updates
Author Tags
Qualifiers
- Research-article
- Research
- Refereed limited
Conference
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 36Total Downloads
- Downloads (Last 12 months)21
- Downloads (Last 6 weeks)3
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inFull Access
View options
View or Download as a PDF file.
PDFeReader
View online with eReader.
eReaderHTML Format
View this article in HTML Format.
HTML Format