Text Analysis Pipelines (Record no. 57353)

000 -LEADER
fixed length control field 03420nam a22005775i 4500
001 - CONTROL NUMBER
control field 978-3-319-25741-9
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112220.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 151202s2015 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319257419
-- 978-3-319-25741-9
082 04 - CLASSIFICATION NUMBER
Call Number 025.04
100 1# - AUTHOR NAME
Author Wachsmuth, Henning.
245 10 - TITLE STATEMENT
Title Text Analysis Pipelines
Sub Title Towards Ad-hoc Large-Scale Text Mining /
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2015.
300 ## - PHYSICAL DESCRIPTION
Number of Pages XX, 302 p. 74 illus. in color.
490 1# - SERIES STATEMENT
Series statement Lecture Notes in Computer Science,
520 ## - SUMMARY, ETC.
Summary, etc This 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 peoples' 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.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-25741-9
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
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-- Springer International Publishing :
-- Imprint: Springer,
-- 2015.
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-- computer
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-- rdamedia
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-- online resource
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-- text file
-- PDF
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computer science.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computers.
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-- Mathematical logic.
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-- Database management.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Information storage and retrieval.
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-- Artificial intelligence.
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-- Computer Science.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Information Storage and Retrieval.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Information Systems Applications (incl. Internet).
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-- Artificial Intelligence (incl. Robotics).
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-- Mathematical Logic and Formal Languages.
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-- Database Management.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computation by Abstract Devices.
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-- 0302-9743 ;
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