Ontology-Driven Information Extraction with OntoSyphon Export

@incollection{citeulike:2028746, abstract = {The Semantic Web's need for machine understandable content has led researchers to attempt to automatically acquire such content from a number of sources, including the web. To date, such research has focused on ” document-driven” systems that individually process a small set of documents, annotating each with respect to a given ontology. This paper introduces OntoSyphon, an alternative that strives to more fully leverage existing ontological content while scaling to extract comparatively shallow content from millions of documents. OntoSyphon operates in an ” ontology-driven” manner: taking any ontology as input, OntoSyphon uses the ontology to specify web searches that identify possible semantic instances, relations, and taxonomic information. Redundancy in the web, together with information from the ontology, is then used to automatically verify these candidate instances and relations, enabling OntoSyphon to operate in a fully automated, unsupervised manner. A prototype of OntoSyphon is fully implemented and we present experimental results that demonstrate substantial instance learning in a variety of domains based on independently constructed ontologies. We also introduce new methods for improving instance verification, and demonstrate that they improve upon previously known techniques.}, author = {Mcdowell, Luke and Cafarella, Michael}, citeulike-article-id = {2028746}, citeulike-linkout-0 = {http://dx.doi.org/10.1007/11926078_31}, citeulike-linkout-1 = {http://dx.doi.org/http://dx.doi.org/10.1007/11926078_31}, citeulike-linkout-2 = {http://dx.doi.org/10.1007/11926078_31}, doi = {10.1007/11926078_31}, journal = {The Semantic Web - ISWC 2006}, keywords = {annotation, information\_extraction, ontologies, semantics, system}, pages = {428--444}, posted-at = {2007-11-30 14:19:56}, priority = {3}, title = {Ontology-Driven Information Extraction with OntoSyphon}, url = {http://dx.doi.org/10.1007/11926078_31}, year = {2006} }

TY - CHAP ID - citeulike:2028746 L3 - citeulike-article-id:2028746 N2 - The Semantic Web’s need for machine understandable content has led researchers to attempt to automatically acquire such content from a number of sources, including the web. To date, such research has focused on “document-driven” systems that individually process a small set of documents, annotating each with respect to a given ontology. This paper introduces OntoSyphon, an alternative that strives to more fully leverage existing ontological content while scaling to extract comparatively shallow content from millions of documents. OntoSyphon operates in an “ontology-driven” manner: taking any ontology as input, OntoSyphon uses the ontology to specify web searches that identify possible semantic instances, relations, and taxonomic information. Redundancy in the web, together with information from the ontology, is then used to automatically verify these candidate instances and relations, enabling OntoSyphon to operate in a fully automated, unsupervised manner. A prototype of OntoSyphon is fully implemented and we present experimental results that demonstrate substantial instance learning in a variety of domains based on independently constructed ontologies. We also introduce new methods for improving instance verification, and demonstrate that they improve upon previously known techniques. JF - The Semantic Web - ISWC 2006 EP - 444 TI - Ontology-Driven Information Extraction with OntoSyphon SP - 428 KW - annotation KW - information_extraction KW - ontologies KW - semantics KW - system AU - Mcdowell, Luke AU - Cafarella, Michael PY - 2006/// UR - http://dx.doi.org/10.1007/11926078_31 ER -