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020 _a9783642207952
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024 7 _a10.1007/978-3-642-20795-2
_2doi
050 4 _aQ334-342
050 4 _aTA347.A78
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
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072 7 _aUYQ
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082 0 4 _a006.3
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245 1 0 _aKnowledge-Driven Multimedia Information Extraction and Ontology Evolution
_h[electronic resource] :
_bBridging the Semantic Gap /
_cedited by Georgios Paliouras, Constantine D. Spyropoulos, George Tsatsaronis.
250 _a1st ed. 2011.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2011.
300 _aIX, 245 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
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_2rda
490 1 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v6050
505 0 _aBootstrapping Ontology Evolution with Multimedia Information Extraction -- Semantic Representation of Multimedia Content -- Semantics Extraction from Images -- Ontology Based Information Extraction from Text -- Logical Formalization of Multimedia Interpretation -- Ontology Population and Enrichment: State of the Art -- Ontology and Instance Matching -- A Survey of Semantic Image and Video Annotation Tools.
520 _aThis book aims to cover the state of the art in the fields of ontology evolution and information extraction from multimedia, while also promoting the synergy between these two fields. The contents stem largely from the research work conducted over a period of three years under the framework of the research project BOEMIE (Bootstrapping Ontology Evolution with Multimedia Information Extraction). The book is designed to provide researchers, practitioners, and students with basic knowledge and skills presenting a sound theoretical framework as well as concrete examples of applications. The book is organized in eight chapters. The first chapter provides an overview of the BOEMIE project and its main achievements. The second chapter presents current approaches to the representation of knowledge about multimedia using ontologies. The following two chapters provide the state of the art in extraction methods for two important types of multimedia content, i.e. image and text. The fifth chapter covers the automated reasoning process, where the authors attempt to bridge content and knowledge in a process inspired by human reasoning based on perception. The next two chapters provide the state of the art in ontology learning, population and matching, while the last chapter gives a survey of tools that are useful for the annotation of multimedia content with semantics, i.e. concepts and relations that have a particular meaning in the application domain.
650 0 _aArtificial intelligence.
_93407
650 0 _aMultimedia systems.
_911575
650 0 _aInformation storage and retrieval systems.
_922213
650 0 _aApplication software.
_9131540
650 0 _aComputational linguistics.
_96146
650 1 4 _aArtificial Intelligence.
_93407
650 2 4 _aMultimedia Information Systems.
_931575
650 2 4 _aInformation Storage and Retrieval.
_923927
650 2 4 _aComputer and Information Systems Applications.
_9131541
650 2 4 _aComputational Linguistics.
_96146
700 1 _aPaliouras, Georgios.
_eeditor.
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_9131542
700 1 _aSpyropoulos, Constantine D.
_eeditor.
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_9131543
700 1 _aTsatsaronis, George.
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_4http://id.loc.gov/vocabulary/relators/edt
_9131544
710 2 _aSpringerLink (Online service)
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783642207945
776 0 8 _iPrinted edition:
_z9783642207969
830 0 _aLecture Notes in Artificial Intelligence,
_x2945-9141 ;
_v6050
_9131546
856 4 0 _uhttps://doi.org/10.1007/978-3-642-20795-2
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