Extracting Enterprise Vocabularies Using Linked Open Data

Presented at: 8th International Semantic Web Conference (ISWC2009)

by Julian Dolby, Achille Fokoue, Aditya Kalyanpur, Edith Schonberg, Kavitha Srinivas

Webpage: http://data.semanticweb.org/pdfs/iswc/2009/in-use/paper143.pdf
Webpage: http://dx.doi.org/10.1007/978-3-642-04930-9_49
Webpage: http://www.springerlink.com/content/l47j623206033872

A common vocabulary is vital to smooth business operation, yet codifying and maintaining an enterprise vocabulary is an arduous, manual task. We describe a process to automatically extract a domain specific vocabulary (terms and types) from unstructured data in the enterprise guided by term definitions in Linked Open Data (LOD). We validate our techniques by applying them to the IT (Information Technology) domain, taking 58 Gartner analyst reports and using two specific LOD sources -- DBpedia and Freebase.

Keywords: Semantic Web

Resource URI on the dog food server: http://data.semanticweb.org/conference/iswc/2009/paper/inuse/143

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