1. Extracting Semantic Relationships Between Wikipedia Articles Lowell Shayn Hawthorne Suzette Stoutenburg Supervisor: Jugal Kalita University of Colorado at Colorado Springs (USA)

2. 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 [16] 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

3. 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

4. Use patterns to acquire relationships

5. 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