Yago: a core of semantic knowledge
Proceedings of the 16th international conference on World Wide Web
Accuracy in Rating and Recommending Item Features
AH '08 Proceedings of the 5th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Consolidating User-Defined Concepts with StYLiD
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
Improving recommendation accuracy based on item-specific tag preferences
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
Ontology-based economics knowledge sharing system
Expert Systems with Applications: An International Journal
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Revyu.com is a live, publicly accessible reviewing and rating Web site, designed to be usable by humans whilst transparently generating machine-readable RDF metadata for the Semantic Web, based on their input. The site uses Semantic Web specifications such as RDF and SPARQL, and the latest Linked Data best practices to create a major node in a potentially Web-wide ecosystem of reviews and related data. Throughout the implementation of Revyu design decisions have been made that aim to minimize the burden on users, by maximizing the reuse of external data sources, and allowing less structured human input (in the form of Web2.0-style tagging) from which stronger semantics can later be derived. Links to external sources such as DBpedia are exploited to create human-oriented mashups at the HTML level, whilst links are also made in RDF to ensure Revyu plays a first class role in the blossoming Web of Data. The site is available at 〈http://revyu.com〉.