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swoogle.umbc/

APIs. Web services. Agent services. Apache/ Tomcat php, myAdmin. Web interface. Focused Crawler. Web. mySQL. Ontology Analyzer. SWD crawler. DB. Jena. Jena. IR engine. Ontology Agents. Ontology Agents. Ontology Agents. Ontology Agents. CGI scripts. SWOs. Ontology discovery.

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swoogle.umbc/

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  1. APIs Webservices Agentservices Apache/Tomcatphp, myAdmin Web interface FocusedCrawler Web mySQL Ontology Analyzer SWD crawler DB Jena Jena IRengine OntologyAgents OntologyAgents OntologyAgents OntologyAgents CGI scripts SWOs Ontology discovery Videofiles Ontology discovery Google SIRE HTML documents Audiofiles SWIs cached files Images SWD = SWO + SWI Swoogle is a crawler based search & retrieval system for semantic web documents (SWDs) in RDF, Owl and DAML. It discovers SWDs and computes their metadata and relations, and stores them in an IR system. The web, like Gaul, is divided into three parts: the regular web (e.g. HTML), Seman- tic Web Ontologies (SWOs), and Semantic Web Instance files (SWIs) SWD Properties Language and level; encoding, number of triples, defined classes, defined properties, & defined individuals; type (SWO, SWI); form (RSS, FOAF, P3P, …); rank; weight; annotations; … SWD Relations SWD Rank Swoogle uses two kinds of crawlers to discover semantic web documents and several analysis agents to compute metadata and relations among documents and ontologies. Metadata is stored in a relational DBMS. A SWD’s rank is a function of its type (SWO/SWI) and the rank and types of the documents to which it’s related. • Binary: R(D1,D2) • IM: D1 owl:imports D2 • IMstar: transitive closure of IM • EX: D1 extends D2 by defining classes or properties subsumed by D2’s • PV: owl:priorVersion & subproperties • TM: D1 uses terms from D2 • IN: D1 uses individual defined in D2 • MAP: D1 maps some of its terms to D2’s • SIM: D1 & D2 are similar • EQ: D1 & D2 are identical • EQV: D1 & D2 have the same triples • Ternary: R(D1,D2,D3) • MP3: D1 maps a term from D2 to D3 using owl:sameClass, etc. http://swoogle.umbc.edu/ Swoogle v1 has ~12K SWDs & 100K relations. v2 will also catalog classes and properties and their metadata and have >1.6M SWDs. SWD IR Engine Swoogle puts documents into a character n-gram based IR engine to compute document similarity and do retrieval from queries Contributors include Tim Finin, Anupam Joshi, Yun Peng, R. Scott Cost, Jim Mayfield, Joel Sachs, Pavan Reddivari, Vishal Doshi, Rong Pan, Li Ding, and Drew Ogle. Partial research support was provided by DARPA contract F30602-00-0591 and by NSF by awards NSF-ITR-IIS-0326460 and NSF-ITR-IDM-0219649. 20 May 2004.

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