Annotea: an open RDF infrastructure for shared Web annotations
Proceedings of the 10th international conference on World Wide Web
The Journal of Machine Learning Research
The myGrid ontology: bioinformatics service discovery
International Journal of Bioinformatics Research and Applications
BiOnMap: a deductive approach for resource discovery
Proceedings of the 10th International Conference on Information Integration and Web-based Applications & Services
A relevance model for a data warehouse contextualized with documents
Information Processing and Management: an International Journal
An active registry for bioinformatics web services
Bioinformatics
Probabilistic models of ranking novel documents for faceted topic retrieval
Proceedings of the 18th ACM conference on Information and knowledge management
Dynamic Taxonomies and Faceted Search: Theory, Practice, and Experience
Dynamic Taxonomies and Faceted Search: Theory, Practice, and Experience
Semantic annotation, indexing, and retrieval
Web Semantics: Science, Services and Agents on the World Wide Web
Semantic annotation for knowledge management: Requirements and a survey of the state of the art
Web Semantics: Science, Services and Agents on the World Wide Web
Ontology refinement for improved information retrieval
Information Processing and Management: an International Journal
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
Feta: a light-weight architecture for user oriented semantic service discovery
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
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Open metadata registries are a fundamental tool for researchers in the Life Sciences trying to locate resources such as web services or databases. While sophisticated standards have been produced for annotating these resources with rich, well-structured metadata, evidence shows that in open registries a majority of annotations simply consists of informal free text descriptions. This reality must be taken into account in order to develop effective techniques for resource discovery in the Life Sciences. In this work we propose a method for resource discovery which is able to exploit such textual descriptions to find relevant resources. It is a requirement-driven approach, in which the user specifies informational needs as a target task and a set of facets of interest, expressed using free text. We have conducted several experiments on resources extracted from the BioCatalogue registry. For a sample set of queries that reflect common Bioinformatics-related research questions, the results show that our method is effective and provides useful answers.