A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Communications of the ACM
An Approach for Measuring Semantic Similarity between Words Using Multiple Information Sources
IEEE Transactions on Knowledge and Data Engineering
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Content-based multimedia information retrieval: State of the art and challenges
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
The Long Tail: Why the Future of Business Is Selling Less of More
The Long Tail: Why the Future of Business Is Selling Less of More
A user-oriented contents recommendation system in peer-to-peer architecture
Expert Systems with Applications: An International Journal
A recommendation system for browsing digital libraries
Proceedings of the 2009 ACM symposium on Applied Computing
An ontology-driven approach for semantic information retrieval on the Web
ACM Transactions on Internet Technology (TOIT)
Personalized Recommendation over a Customer Network for Ubiquitous Shopping
IEEE Transactions on Services Computing
Axiomatic foundations for ranking systems
Journal of Artificial Intelligence Research
A Combined Relevance Feedback Approach for User Recommendation in E-commerce Applications
ACHI '10 Proceedings of the 2010 Third International Conference on Advances in Computer-Human Interactions
Content-based recommendation systems
The adaptive web
A ranking method for multimedia recommenders
Proceedings of the ACM International Conference on Image and Video Retrieval
Automatic preference learning on numeric and multi-valued categorical attributes
Knowledge-Based Systems
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In this paper, we present a new vision of multimedia recommender systems based on an a novel paradigm that combines both analysis of user behavior and semantic descriptors of multimedia objects. In particular, we model recommendation as a two step process: First we propose a model of user behavior, based on a semantic network that captures the necessary knowledge of the domain of interest; second we propose a recommendation strategy based on both this kind of a-priori knowledge and on the current usage patterns, considering the actual and complex structure of multimedia data. We have implemented a prototype that supports our proposed recommendation strategy; eventually a real use of our system based on a 3D interface is presented and discussed.