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Text Analysis Pipelines: Towards Ad-hoc Large-Scale Text Mining Henning Wachsmuth Author
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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 … More...

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Text Analysis Pipelines: Towards Ad-hoc Large-Scale Text Mining Henning Wachsmuth Author
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9783319257419

Details of the book - Text Analysis Pipelines: Towards Ad-hoc Large-Scale Text Mining Henning Wachsmuth Author


EAN (ISBN-13): 9783319257419
Publishing year: 12
Publisher: Springer International Publishing Digital >16

Book in our database since 2016-02-01T22:14:05+00:00 (London)
Detail page last modified on 2023-12-12T22:23:41+00:00 (London)
ISBN/EAN: 9783319257419

ISBN - alternate spelling:
978-3-319-25741-9
Alternate spelling and related search-keywords:
Book author: wachsmuth, henning

Information from Publisher

Author: Henning Wachsmuth
Title: Theoretical Computer Science and General Issues; Lecture Notes in Computer Science; Text Analysis Pipelines - Towards Ad-hoc Large-Scale Text Mining
Publisher: Springer; Springer International Publishing
302 Pages
Publishing year: 2015-12-02
Cham; CH
Language: English
53,49 € (DE)
55,00 € (AT)
59,00 CHF (CH)
Available
XX, 302 p. 74 illus. in color.

EA; E107; eBook; Nonbooks, PBS / Informatik, EDV/Informatik; Informationsrückgewinnung, Information Retrieval; Verstehen; Efficienciy and effectiveness; Information extraction; Machine learning; Natural language processing; Text minig; Adaptive scheduling; Argumentation structure; Artificial intelligence; Big data; Domain robustness; Information structure; Language function analysis; Online learning; Parallelization; Pipeline; Pipeline design; Sentiment analysis; Similarity; Text analysis; Text classification; B; Information Storage and Retrieval; Computer and Information Systems Applications; Artificial Intelligence; Formal Languages and Automata Theory; Database Management; Theory of Computation; Computer Science; Data Warehousing; Angewandte Informatik; Künstliche Intelligenz; Theoretische Informatik; Datenbanken; BC

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.


Includes supplementary material: sn.pub/extras

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