Matches in ScholarlyData for { <https://w3id.org/scholarlydata/inproceedings/eswc2010/paper/phd_symposium/22> ?p ?o. }
Showing items 1 to 13 of
13
with 100 items per page.
- 22 creator georgeta-bordea.
- 22 type InProceedings.
- 22 label "Concept Extraction Applied to the Task of Expert Finding".
- 22 sameAs 22.
- 22 abstract "The Semantic Web uses formal ontologies as a key instrument that adds structure to the underlying data, but building domain specific ontologies is still a difficult, time consuming and error-prone process because most information is currently available as free-text or semi-structured text. Therefore the development of fast and cheap solutions for ontology learning from text is a key factor for the success and large scale adoption of the Semantic Web. Ontology development is primarily concerned with the definition of concepts and relations between them, so one of the fundamental research problems related to ontology learning is the reliable extraction of concepts from text. To investigate this research problem we will focus on the expert finding application, i.e. the reliable extraction of expertise topics from relevant text that can be assigned to individuals in an organization.".
- 22 hasAuthorList authorList.
- 22 isPartOf proceedings.
- 22 keyword "concept extraction".
- 22 keyword "expertise mining".
- 22 keyword "expertise topics".
- 22 keyword "information extraction".
- 22 keyword "text mining".
- 22 title "Concept Extraction Applied to the Task of Expert Finding".