Abstract
Most research work on news mining nowadays covers phrase and topic level. A few works conducted on logical level mainly focus on personalized news service and no special efforts are put on the applications of ontology techniques on deep news mining. In this paper, we demonstrate a whole strategy for deeply understanding event-focused news taking the advantage of ontology representation and ontology reasoning. We propose an ontology-enriched news deep understanding framework ONDU which addresses the following problems: (1) how to transfer parsed news content into logical triples by using domain ontology. (2) The application of ONDU based on the reasoning results from the ontology reasoner TrOWL over the RDF data expressing the news. Through this whole strategy we can detect the inconsistence among multiple news articles and compare the different information implied in different news. We can even integrate a set of news content through merging the RDF data. The empirical experiment conducted on news from several portals shows the effectiveness and usefulness of our method.KeywordsOntologyreasoningnews miningtext understandingTrOWL
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
