- Extracting Enterprise Vocabularies Using Linked Open Data
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 en- terprise guided by term definitions in Linked Open Data (LOD). We validate our techniques by applying them to the IT (Information Tech- nology) domain, taking 58 Gartner analyst reports and using two specific LOD sources – DBpedia and Freebase. We show initial findings that ad- dress the generalizability of these techniques for vocabulary extraction in new domains, such as the energy industry.
IBM Watson Research Center
- Guerilla science: what can we do in 10 days?
I recently invited participants in the upcoming e-Biosphere conference
(June 1-3, London) to join me in a collective demonstration of the
semantic web in action.
The short story is that we'll be integrating wildlife observations with
background biodiversity data to enable as many interesting queries (e.g.,
"show species out of range") as we can.
The concept we're trying to illustrate: a global human sensor net
- "E Pluribus Unum", or "Inversely Functional Identity", or "Smooshing Without the Stickiness" (re-updated)
- A New Constellation in the Linking Open Data (LOD) Sky » AI3:::Adaptive Information
Class-level Mappings Now Generalize Semantic Web Connectivity