MAFRA - A MApping FRAmework for Distributed Ontologies
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Ontology mapping: the state of the art
The Knowledge Engineering Review
Trends and issues in establishing interoperability among knowledge organization systems
Journal of the American Society for Information Science and Technology
Ontology Matching
Building a terminology network for search: the KoMoHe project
DCMI '08 Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications
Evaluating the semantic web: a task-based approach
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Matching multi-lingual subject vocabularies
ECDL'09 Proceedings of the 13th European conference on Research and advanced technology for digital libraries
Save up to 99% of your time in mapping validation
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems: Part II
Domains and context: First steps towards managing diversity in knowledge
Web Semantics: Science, Services and Agents on the World Wide Web
Merging Controlled Vocabularies for More Efficient Subject-Based IR Systems
International Journal of Knowledge Management
Ontologies and terminologies: Continuum or dichotomy?
Applied Ontology - Ontologies and Terminologies: Continuum or Dichotomy?
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Knowledge organization systems (KOS), like thesauri and other controlled vocabularies, are used to provide subject access to information systems across the web. Due to the heterogeneity of these systems, mapping between vocabularies becomes crucial for retrieving relevant information. However, mapping thesauri is a laborious task, and thus big efforts are being made to automate the mapping process. This paper examines two mapping approaches involving the agricultural thesaurus AGROVOC, one machine-created and one human created. We are addressing the basic question "What are the pros and cons of human and automatic mapping and how can they complement each other?" By pointing out the difficulties in specific cases or groups of cases and grouping the sample into simple and difficult types of mappings, we show the limitations of current automatic methods and come up with some basic recommendations on what approach to use when.