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Integrating keywords and semantics on document annotation and search

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dc.contributor.author Bikakis, N en
dc.contributor.author Giannopoulos, G en
dc.contributor.author Dalamagas, T en
dc.contributor.author Sellis, T en
dc.date.accessioned 2014-03-01T02:46:51Z
dc.date.available 2014-03-01T02:46:51Z
dc.date.issued 2010 en
dc.identifier.issn 03029743 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/32887
dc.subject Document Annotations en
dc.subject GoNTogle en
dc.subject Hybrid Search en
dc.subject Keyword Search en
dc.subject Ontology based Retrieval en
dc.subject Semantic Annotation en
dc.subject Semantic Search en
dc.subject.other Document annotation en
dc.subject.other GoNTogle en
dc.subject.other Hybrid search en
dc.subject.other Keyword search en
dc.subject.other Ontology based Retrieval en
dc.subject.other Semantic Annotation en
dc.subject.other Semantic Search en
dc.subject.other Internet en
dc.subject.other Ontology en
dc.subject.other Search engines en
dc.subject.other Semantic Web en
dc.subject.other Semantics en
dc.subject.other Information retrieval en
dc.title Integrating keywords and semantics on document annotation and search en
heal.type conferenceItem en
heal.identifier.primary 10.1007/978-3-642-16949-6_19 en
heal.identifier.secondary http://dx.doi.org/10.1007/978-3-642-16949-6_19 en
heal.publicationDate 2010 en
heal.abstract This paper describes GoNTogle, a framework for document annotation and retrieval, built on top of Semantic Web and IR technologies. GoNTogle supports ontology-based annotation for documents of several formats, in a fully collaborative environment. It provides both manual and automatic annotation mechanisms. Automatic annotation is based on a learning method that exploits user annotation history and textual information to automatically suggest annotations for new documents. GoNTogle also provides search facilities beyond the traditional keyword-based search. A flexible combination of keyword-based and semantic-based search over documents is proposed in conjunction with advanced ontology-based search operations. The proposed methods are implemented in a fully functional tool and their effectiveness is experimentally validated. © 2010 Springer-Verlag. en
heal.journalName Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) en
dc.identifier.doi 10.1007/978-3-642-16949-6_19 en
dc.identifier.volume 6427 LNCS en
dc.identifier.issue PART 2 en
dc.identifier.spage 921 en
dc.identifier.epage 938 en


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