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[null,"1.","Record Nr.",null,"UNINA9910782332603321"]
[null,null,"Titolo",null,"Ontology learning and population [[electronic resource] ] : bridging the gap between text and knowledge / / edited by Paul Buitelaar and Philipp Cimiano"]
[null,null,"Pubbl/distr/stampa",null,"Amsterdam, : Ios Press, 2008"]
[null,null,"ISBN",null,"6611733558"]
[{"$nulls":4},"1-281-73355-5"]
[{"$nulls":4},"9786611733551"]
[{"$nulls":4},"1-60750-296-8"]
[{"$nulls":4},"600-00-0509-1"]
[{"$nulls":4},"1-4337-1130-3"]
[null,null,"Descrizione fisica",null,"1 online resource (292 p.)"]
[null,null,"Collana",null,"Frontiers in artificial intelligence and applications ; ; v. 167"]
[null,null,"Disciplina",null,"006.33"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Expert systems (Computer science)"]
[{"$nulls":4},"Information retrieval"]
[{"$nulls":4},"Knowledge acquisition (Expert systems)"]
[{"$nulls":4},"Machine learning"]
[{"$nulls":4},"Natural language processing (Computer science)"]
[{"$nulls":4},"Ontology"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Description based upon print version of record."]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,null,"Nota di contenuto",null,"Title page; On the \"\"Ontology\"\" in Ontology Learning; Foreword; Contents; Extracting Terms and Synonyms; Taxonomy and Concept Learning; Learning Relations; Ontology Population; Methodology; Evaluation; Author Index"]
[null,null,null,"Sommario/riassunto","The promise of the Semantic Web is that future web pages will be annotated not only with bright colors and fancy fonts as they are now, but with annotation extracted from large domain ontologies that specify, to a computer in a way that it can exploit, what information is contained on the given web page. The presence of this information will allow software agents to examine pages and to make decisions about content as humans are able to do now. The classic method of building an ontology is to gather a committee of experts in the domain to be modeled by the ontology, and to have this committee"]