Text analysis pipelines [electronic resource] : towards ad-hoc large scale text mining / Henning Wachsmuth.
2015
QA76.9.T48
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Title
Text analysis pipelines [electronic resource] : towards ad-hoc large scale text mining / Henning Wachsmuth.
Author
Wachsmuth, Henning.
ISBN
9783319257419 electronic book
3319257412 electronic book
9783319257402
3319257412 electronic book
9783319257402
Published
Cham : Springer, [2015]
Copyright
©2015
Language
English
Description
1 online resource (xx, 302 pages) : illustrations.
Call Number
QA76.9.T48
Dewey Decimal Classification
025.04
Summary
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 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.
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Series
Lecture notes in computer science ; 9383.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.
LNCS sublibrary. SL 1, Theoretical computer science and general issues.
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