Domain-Specific Modeling: Towards a Food and Drink Gazetteer
Our goal is to build a Food and Drink (FD) gazetteer that can serve for classification of general, FD-related concepts, efficient faceted search or automated semantic enrichment. Fully supervised design of a domain-specific models ex novo is not scalable. Integration of several ready knowledge bases is tedious and does not ensure coverage. Completely data-driven approaches require a large amount of training data, which is not always available. For general domains (such as the FD domain), re-using encyclopedic knowledge bases like Wikipedia may be a good idea. We propose here a semi-supervised approach that uses a restricted Wikipedia as a base for the modeling, achieved by selecting a domain-relevant Wikipedia category as root for the model and all its subcategories, combined with expert and data-driven pruning of irrelevant categories.
KeywordsCategorization Wikipedia Wikipedia categories Gazetteer Europeana Cultural heritage Concept extraction
The research presented in this paper was carried out as part of the Europeana Food and Drink project, co-funded by the European Commission within the ICT Policy Support Programme (CIP-ICT-PSP-2013-7) under Grant Agreement no. 621023.
- 1.Agirre, E., Barrena, A., De Lacalle, OL., Soroa, A., Fern, S., Stevenson, M.: Matching cultural heritage items to Wikipedia (2012)Google Scholar
- 2.Alexiev, V.: Europeana Food and Drink Classification Scheme, Europeana Food and Drink project, Deliverable D2.2 (2015). http://vladimiralexiev.github.io/pubs/Europeana-Food-and-Drink-Classification-Scheme-(D2.2).pdf
- 3.Cheng, CP., Lau, GT., Pan, J, Law, KH., Jones, A.: Domain-Specific ontology mapping by corpus-based semantic similarityGoogle Scholar
- 4.Fridman Noy, N., Musen, MA.: Domain-specific ontology mapping by corpus-based semantic similarity. In: Workshop on Ontology Management at the 16th National Conference on Artificial Intelligence (AAAI 1999) (1999)Google Scholar
- 5.Medelyan, O., Manion, S., Broekstra, J., Divoli, A., Huang, A.-L., Witten, I.H.: Constructing a focused taxonomy from a document collection. In: Cimiano, P., Corcho, O., Presutti, V., Hollink, L., Rudolph, S. (eds.) ESWC 2013. LNCS, vol. 7882, pp. 367–381. Springer, Heidelberg (2013) CrossRefGoogle Scholar
- 7.Miles, A., Bechhofer, S.: SKOS simple knowledge organization system reference. In: W3C Recommendation (2009)Google Scholar
- 8.Mousavi, H., Kerr, D., Iseli, M., Zaniolo, C.: Harvesting domain specific ontologies from text. In: ICSC 2014, pp. 211–218 (2014)Google Scholar
- 9.Mousavi, H., Kerr, D., Iseli, M., Zaniolo, C.: OntoHarvester: an unsupervised ontology generator from free text. CSD Technical report #130003, University of California Los Angeles (2013)Google Scholar
- 10.Parekh, V., Gwo, J.: Mining domain specific texts and glossaries to evaluate and enrich domain ontologies. In: Proceedings of the International Conference of Information and Knowledge Engineering (2004)Google Scholar
- 11.Pinto, HS., Martins, JP.: A methodology for ontology integration In: Proceedings of the 1st International Conference on Knowledge Capture, K-CAP 2001 (2001)Google Scholar
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