Presentation on theme: "Extracting Semantic Relationships Between Wikipedia Articles Lowell Shayn Hawthorne Suzette Stoutenburg Supervisor: Jugal Kalita University of Colorado."— Presentation transcript:
Extracting Semantic Relationships Between Wikipedia Articles Lowell Shayn Hawthorne Suzette Stoutenburg Supervisor: Jugal Kalita University of Colorado at Colorado Springs (USA)
Acquiring Relationships Between Wikipedia Articles Wikipedia is arguably the largest source of collaboratively developed knowledge in the world −But Wikipedia is largely unstructured and therefore unavailable for use by most software systems In the recent years, there has been increasing research in the use of Wikipedia as a broadly applicable lexical semantic resource −Most approaches extract information from Wikipedia by harnessing implicit semantics in the syntactic structures [4, 10] −One approach has been proposed to explicitly express the relationships between links  though this has not yet been implemented −Other approaches use natural language processing techniques to extract knowledge from the structures of Wikipedia [5, 10, 14, 15] but none of these have focused on assigning meaning to the links between articles
Approach We extract the meaning of relationships between Wikipedia articles using natural language processing techniques We use regular expressions to detect linguistic patterns and infer relationships between each linked article pair Preliminary results are competitive for some relationships with high precision Use of regular expressions over parts of speech is feasible for knowledge extraction
We All Want a Good Relationship Ontology alignment can support service composition, service mediation and enterprise integration Ontology alignment of key words and metadata about a user’s web searches could link buyers to desired products and fulfill sales online
Your consent to our cookies if you continue to use this website.