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SemNews: A Semantic News Framework

http://semnews.umbc.edu. Fact Repository Interface. Fact Repository. Language Processing. Data Aggregators. 1. 11. 2. Provides RDF version of the news. OntoSem. RSS Aggregator. Ontology & Instance browser. 3. 4. NL Text. Facts from NL. OntoSem. TMR. News Feeds. TMRs. FR.

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SemNews: A Semantic News Framework

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  1. http://semnews.umbc.edu Fact Repository Interface Fact Repository Language Processing Data Aggregators 1 11 2 Provides RDF version of the news. OntoSem RSS Aggregator Ontology & Instance browser 3 4 NL Text Facts from NL OntoSem TMR News Feeds TMRs FR NLP Tools TMRs In OWL Text Search 12 RDQL Query Natural Language 13 6 RDF/OWL 5 WWW OntoSem2OWL Swoogle Index 14 Semantic Web 9 Text Images Audio video Ontologies Instances triples Dekade Editor Lexicon OntoSem2OWL 7 Ontology OWL Ontology OntoSem Ontology (OWL) Inferred Triples Semantic RSS 15 10 8 Knowledge Editor Environment TMR Web of documents Web of data Semantic Web Tools SemNews: A Semantic News Framework Akshay Java, Tim Finin, Sergei Nirenburg System Architecture Browsing Facts Semantacizing RSS View structured representation of RSS news stories. SemNews is a framework for processing RSS summaries of news using OntoSem, a sophisticated NLP tool. The text meaning representation is then exported in OWL. The fact repository constructed can be explored and queried. Browse facts not just news. Ontologically linked News Agent Understandable News Semantic Queries Semantic Alerts Tracking Named Entities RDQL Find news stories by browsing through the OntoSem ontology. Structured queries over text converted to RDF representation. • Intelligent agents need knowledge and information. • Majority of content on the Web remains in natural language. • SW can benefit NLP tools in their language understanding task. Alerts can be specified as ontological concepts/ keywords/ RDQL queries. Subscribe to the results as an RSS feed. Find stories about a specific named entity. Conclusions Ontological Semantics OntoSem to OWL • NLP tools can .provide SW annotations that capture the text meaning. • Migrating non web-based KR to SW representation can be lossy. Future Work • OntoSem is a NLP system that processes text and converts them into facts. • Supported by a constructed world model encoded in an rich ontology. • Ontology of over 8000 concepts. • Average 16 properties per concept. • English lexicon of 45000 entries • OntoSem2OWL is a rule based conversion engine that maps frame-based OntoSem ontology, fact repository to OWL. • Over 102189 triples generated. • Importing facts from SW • Inference support. • SemNews web service. http://ebiquity.umbc.edu/

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