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Springer Modeling, Learning, and Processing of Text-Technological Data Structures (370)

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Description

Explore the theoretical foundations and practical applications of natural language text processing with this comprehensive volume from Springer's Studies in Computational Intelligence series. This book addresses the challenges of modelling textual data as a primary information unit of written communication, combining integrated approaches that span both foundational concepts and concrete automatic text processing operations. Researchers, academics, and professionals working across disciplines will find valuable contributions covering a wide range of topics in computational text analysis, making it an essential resource for understanding how to represent, learn from, and process natural language texts in computational systems.

Key Features

Covers theoretical foundations for representing natural language texts as computational data structures.

Includes practical contributions to automatic text processing and information extraction from textual sources.

Published by Springer as part of the Studies in Computational Intelligence series volume 370.

Addresses modelling challenges for texts as primary information units in written communication.

Combines integrated approaches spanning both foundational research and concrete operational methodologies.

Product Specifications

Format
paperback
Domain
Amazon UK
Release Date
27 November 2013
Listed Since
26 December 2013

Barcode

No barcode data available

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