Perceptual organization and the representation of natural form
Artificial Intelligence
Conceptual Spaces: The Geometry of Thought
Conceptual Spaces: The Geometry of Thought
Description Logics for Information Integration
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part II
A software framework for matchmaking based on semantic web technology
WWW '03 Proceedings of the 12th international conference on World Wide Web
Information Sharing on the Semantic Web
Information Sharing on the Semantic Web
Transparent access to multiple bioinformatics information sources
IBM Systems Journal - Deep computing for the life sciences
Natural Language Engineering
SemRank: ranking complex relationship search results on the semantic web
WWW '05 Proceedings of the 14th international conference on World Wide Web
A Flexible Ontology Reasoning Architecture for the Semantic Web
IEEE Transactions on Knowledge and Data Engineering
OWL-Eu: Adding customised datatypes into OWL
Web Semantics: Science, Services and Agents on the World Wide Web
Ontology–Based representation and query colour descriptions from botanical documents
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, COA, and ODBASE - Volume Part II
Hybrid model for semantic similarity measurement
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, COA, and ODBASE - Volume Part II
Information fusion in taxonomic descriptions
Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
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Information integration and retrieval have been important problems for many information systems — it is hard to combine new information with any other piece of related information we already possess, and to make them both available for application queries. Many ontology-based applications are still cautious about integrating and retrieving information from natural language (NL) documents, preferring structured or semi-structured sources. In this paper, we investigate how to use ontologies to facilitate integrating and querying information on parallel leaf shape descriptions from NL documents. Our approach takes advantage of ontologies to precisely represent the semantics in shape description, to integrates parallel descriptions according to their semantic distances, and to answer shape-related species identification queries. From this highly specialised domain, we learn a set of more general methodological rules, which could be useful in other domains.