Finding Topic-centric Identified Experts based on Full Text Analysis
Hanmin Jung, Mikyoung Lee, In-Su Kang, Seungwoo Lee, Won-Kyung Sung · 2008
Abstract. This paper shows a method for finding topic-centric experts from open access metadata and full text documents. Topic-centric information including experts is served on OntoFrame, which is a Semantic Web-based academic research information service supporting R&D activities. URI schemebased OntoFrame provides three entity pages: topic, person, and event. ‘Persons by Topic ’ in topic page lists up topic-centric identified experts. SPARQL query is used to retrieve them from RDF triple store through backward chaining. We gathered CiteSeer open access metadata and full text documents with the amount of about 110,000 papers. Using about 160,000 abundant topics, OntoFrame now serves topic-centric identified experts and relevant information acquired by full text analysis. 1