Toward principles for the design of ontologies used for knowledge sharing
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Ontology ranking based on the analysis of concept structures
Proceedings of the 3rd international conference on Knowledge capture
Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. (Advanced Information and Knowledge Processing)
Searching ontologies based on content: experiments in the biomedical domain
Proceedings of the 4th international conference on Knowledge capture
Ontology Evaluation through Text Classification
Advances in Web and Network Technologies, and Information Management
Finding and ranking knowledge on the semantic web
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Fast and simple semantic class assignment for biomedical text
BioNLP '11 Proceedings of BioNLP 2011 Workshop
An empirical study of vocabulary relatedness and its application to recommender systems
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
International Journal of Knowledge-based and Intelligent Engineering Systems - Selected papers of KES2012-Part 1 of 2
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In recent years, ontologies have become an essential tool to structure and reuse the exponential growth of information in the Web. As the number of publicly available ontologies increases, researchers face the problem of finding the ontology (or ontologies) which provides the best coverage for a particular context. In this paper, we propose an approach to automatically recommend the best ontology for an initial set of terms. The approach is based on measuring the adequacy of the ontology according to three different criteria: (1) How well the ontology covers the given terms, (2) the semantic richness of the ontology and, importantly, (3) the popularity of the ontology in the Web 2.0. In order to evaluate this approach, we implemented a prototype to recommend ontologies in the biomedical domain. Results show the importance of using collaborative knowledge in the field of ontology recommendation.