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200 10$aAdvanced Applications of Natural Language Processing for Performing Information Extraction /$fby Mário Rodrigues, António Teixeira
205   $a1st ed. 2015.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2015.
215   $a1 online resource (82 p.)
225 1 $aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,$x2191-737X
300   $aDescription based upon print version of record.
311   $a3-319-15562-8 
320   $aIncludes bibliographical references and index.
327   $aIntroduction -- Data Gathering, Preparation and Enrichment -- Identifying things, relations, and semantizing data -- Extracting Relevant Information Using a Given Semantic -- Application Examples -- Conclusion.
330   $aThis book explains how can be created information extraction (IE) applications that are able to tap the vast amount of relevant information available in natural language sources: Internet pages, official documents such as laws and regulations, books and newspapers, and social web. Readers are introduced to the problem of IE and its current challenges and limitations, supported with examples. The book discusses the need to fill the gap between documents, data, and people, and provides a broad overview of the technology supporting IE. The authors present a generic architecture for developing systems that are able to learn how to extract relevant information from natural language documents, and illustrate how to implement working systems using state-of-the-art and freely available software tools. The book also discusses concrete applications illustrating IE uses.   ·         Provides an overview of state-of-the-art technology in information extraction (IE), discussing achievements and limitations for the software developer and providing references for specialized literature in the area ·         Presents a comprehensive list of freely available, high quality software for several subtasks of IE and for several natural languages ·         Describes a generic architecture that can learn how to extract information for a given application domain.
410  0$aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,$x2191-737X
606   $aNatural language processing (Computer science)
606   $aComputational linguistics
606   $aSignal processing
606   $aImage processing
606   $aSpeech processing systems
606   $aNatural Language Processing (NLP)$3https://scigraph.springernature.com/ontologies/product-market-codes/I21040
606   $aComputational Linguistics$3https://scigraph.springernature.com/ontologies/product-market-codes/N22000
606   $aSignal, Image and Speech Processing$3https://scigraph.springernature.com/ontologies/product-market-codes/T24051
615  0$aNatural language processing (Computer science)
615  0$aComputational linguistics.
615  0$aSignal processing.
615  0$aImage processing.
615  0$aSpeech processing systems.
615 14$aNatural Language Processing (NLP).
615 24$aComputational Linguistics.
615 24$aSignal, Image and Speech Processing.
676   $a006.35
700   $aRodrigues$b Mário$4aut$4http://id.loc.gov/vocabulary/relators/aut$0721036
702   $aTeixeira$b António$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910299813503321
996   $aAdvanced Applications of Natural Language Processing for Performing Information Extraction$92542727
997   $aUNINA