Class-based n-gram models of natural language
Computational Linguistics
Swoogle: a search and metadata engine for the semantic web
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Content Ontology Design Patterns as Practical Building Blocks for Web Ontologies
ER '08 Proceedings of the 27th International Conference on Conceptual Modeling
Embedding Knowledge Patterns into OWL
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
An approach for the semantic interoperability of ISO EN 13606 and OpenEHR archetypes
Journal of Biomedical Informatics
Enriching the gene ontology via the dissection of labels using the ontology pre-processor language
EKAW'10 Proceedings of the 17th international conference on Knowledge engineering and management by the masses
The OWL API: A Java API for OWL ontologies
Semantic Web
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ICOST'11 Proceedings of the 9th international conference on Toward useful services for elderly and people with disabilities: smart homes and health telematics
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ARES'11 Proceedings of the IFIP WG 8.4/8.9 international cross domain conference on Availability, reliability and security for business, enterprise and health information systems
Automatic verbalisation of SNOMED classes using OntoVerbal
AIME'11 Proceedings of the 13th conference on Artificial intelligence in medicine
Inspecting regularities and irregularities in SNOMED-CT
Proceedings of the 4th International Workshop on Semantic Web Applications and Tools for the Life Sciences
Clinical data interoperability based on archetype transformation
Journal of Biomedical Informatics
Engineering use cases for modular development of ontologies in OWL
Applied Ontology - Modularity in Ontologies
"Hidden semantics": what can we learn from the names in an ontology?
INLG '12 Proceedings of the Seventh International Natural Language Generation Conference
Measuring the level of activity in community built bio-ontologies
Journal of Biomedical Informatics
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The increasing interest in biomedical ontologies has provoked the development of a significant number of ontologies, and many more are expected to be produced in the near future. A significant proportion of such ontologies have not been created by computer scientists or ontology engineers, but by domain experts. Many such ontologies are rich in implicit knowledge, but are really just plain taxonomies and controlled vocabularies, with little axiomatization. Many of these ontologies have much information within the labels of the classes. There is a great deal of knowledge about the entities described within such labels and text definitions held on classes; these are useful for human users, but not for machine processing. In previous work we proposed a process for enriching ontologies, which included the analysis of such labels, the identification of lexical patterns and the design of corresponding knowledge patterns. However, this process relied on manual intervention. In this paper we present a method to analyze and extract unused information contained in the structure of the labels in biomedical ontologies. The aim of this method is to improve the source ontology. The first step is the identification of lexical patterns based on repetitions of sets of words. Second, such lexical patterns will be examined in existing biomedical ontologies to identify whether those patterns are referencing existing ontological entities. Finally, the results obtained with relevant biomedical ontologies are presented and discussed.