Using collaborative filtering to weave an information tapestry
Communications of the ACM - Special issue on information filtering
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
GroupLens: an open architecture for collaborative filtering of netnews
CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Social information filtering: algorithms for automating “word of mouth”
CHI '95 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
PHOAKS: a system for sharing recommendations
Communications of the ACM
Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Experience with personalization of Yahoo!
Communications of the ACM
Explaining collaborative filtering recommendations
CSCW '00 Proceedings of the 2000 ACM conference on Computer supported cooperative work
Mining customer product ratings for personalized marketing
Decision Support Systems - Special issue: Web data mining
Semantic Feedback for Hybrid Recommendations in Recommendz
EEE '05 Proceedings of the 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service (EEE'05) on e-Technology, e-Commerce and e-Service
IEEE Transactions on Knowledge and Data Engineering
Statistics for Engineering and the Sciences (5th Edition)
Statistics for Engineering and the Sciences (5th Edition)
Addressing cold-start problem in recommendation systems
Proceedings of the 2nd international conference on Ubiquitous information management and communication
An MHP framework to provide intelligent personalized recommendations about digital TV contents
Software—Practice & Experience
A random walk method for alleviating the sparsity problem in collaborative filtering
Proceedings of the 2008 ACM conference on Recommender systems
An ontology, intelligent agent-based framework for the provision of semantic web services
Expert Systems with Applications: An International Journal
Automatic generation of semantically enriched web pages by a text mining approach
Expert Systems with Applications: An International Journal
Learning and inferencing in user ontology for personalized Semantic Web search
Information Sciences: an International Journal
The wisdom of the few: a collaborative filtering approach based on expert opinions from the web
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Use of social network information to enhance collaborative filtering performance
Expert Systems with Applications: An International Journal
Developing an ontology-supported information integration and recommendation system for scholars
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
OntoIAS: An ontology-supported information agent shell for ubiquitous services
Expert Systems with Applications: An International Journal
Ontology learning from biomedical natural language documents using UMLS
Expert Systems with Applications: An International Journal
Foafing the music: bridging the semantic gap in music recommendation
ISWC'06 Proceedings of the 5th international conference on The Semantic Web
OWLPath: An OWL Ontology-Guided Query Editor
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Medicine expert system dynamic Bayesian Network and ontology based
Expert Systems with Applications: An International Journal
Financial news semantic search engine
Expert Systems with Applications: An International Journal
Knowledge-Based Systems
International Journal of Organizational and Collective Intelligence
Creating a semantically-enhanced cloud services environment through ontology evolution
Future Generation Computer Systems
Hybrid recommendation approaches for multi-criteria collaborative filtering
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
With the advent of the Social Web and the growing popularity of Web 2.0 applications, recommender systems are gaining momentum. The recommendations generated by these systems aim to provide end users with suggestions about information items, social elements, products or services that are likely to be of their interest. The traditional syntactic-based recommender systems suffer from a number of shortcomings that hamper their effectiveness. As semantic technologies mature, they provide a consistent and reliable basis for dealing with data at the knowledge level. Adding semantically empowered techniques to recommender systems can significantly improve the overall quality of recommendations. In this work, a hybrid recommender system based on knowledge and social networks is presented. Its evaluation in the cinematographic domain yields very promising results compared to state-of-the-art solutions.