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000745410 020__ $$a9783319257419$$qelectronic book
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000745410 050_4 $$aQA76.9.T48
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000745410 08204 $$a025.04$$223
000745410 1001_ $$aWachsmuth, Henning.$$4aut
000745410 24510 $$aText analysis pipelines$$h[electronic resource] :$$btowards ad-hoc large scale text mining /$$cHenning Wachsmuth.
000745410 264_1 $$aCham :$$bSpringer,$$c[2015]
000745410 264_4 $$c©2015
000745410 300__ $$a1 online resource (xx, 302 pages) :$$billustrations.
000745410 336__ $$atext$$btxt$$2rdacontent
000745410 337__ $$acomputer$$bc$$2rdamedia
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000745410 4901_ $$aLNCS sublibrary. SL 1, Theoretical computer science and general issues
000745410 506__ $$aAccess limited to authorized users.
000745410 520__ $$aThis monograph proposes a comprehensive and fully automatic approach to designing text analysis pipelines for arbitrary information needs that are optimal in terms of run-time efficiency and that robustly mine relevant information from text of any kind. Based on state-of-the-art techniques from machine learning and other areas of artificial intelligence, novel pipeline construction and execution algorithms are developed and implemented in prototypical software. Formal analyses of the algorithms and extensive empirical experiments underline that the proposed approach represents an essential step towards the ad-hoc use of text mining in web search and big data analytics. Both web search and big data analytics aim to fulfill peoplesℓ́ℓ needs for information in an adhoc manner. The information sought for is often hidden in large amounts of natural language text. Instead of simply returning links to potentially relevant texts, leading search and analytics engines have started to directly mine relevant information from the texts. To this end, they execute text analysis pipelines that may consist of several complex information-extraction and text-classification stages. Due to practical requirements of efficiency and robustness, however, the use of text mining has so far been limited to anticipated information needs that can be fulfilled with rather simple, manually constructed pipelines.
000745410 650_0 $$aData mining.
000745410 650_0 $$aText processing (Computer science)
000745410 650_0 $$aComputer science.
000745410 650_0 $$aComputers.
000745410 650_0 $$aLogic, Symbolic and mathematical.
000745410 650_0 $$aDatabase management.
000745410 650_0 $$aInformation storage and retrieval
000745410 650_0 $$aArtificial intelligence.
000745410 830_0 $$aLecture notes in computer science ;$$v9383.
000745410 830_0 $$aLNCS sublibrary.$$nSL 1,$$pTheoretical computer science and general issues.
000745410 85280 $$bebk$$hSpringerLink
000745410 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-25741-9$$zOnline Access$$91397441.1
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000745410 980__ $$aEBOOK
000745410 980__ $$aBIB
000745410 982__ $$aEbook
000745410 983__ $$aOnline
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