£111.07

Springer Modeling, Learning, and Processing of Text Data Structures

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Description

Explore the complex world of textual data with Modeling, Learning, and Processing of Text-Technological Data Structures. Published by Springer as part of the Studies in Computational Intelligence series, this volume addresses the growing need to treat text as a primary information unit in written communication. This book provides a comprehensive look at the theoretical foundations required to represent natural language texts. It moves beyond theory to cover the practical, concrete operations involved in automatic text processing. By using an integrated approach, the text connects fundamental concepts with real-world applications in data modeling and machine learning. Researchers across many different disciplines will find value in these contributions. Whether you are studying the mathematical structures of language or the computational methods used to process large datasets, this book serves as a deep dive into the mechanics of textual information. It is a specialized resource for those working in computer science, AI, and machine learning who need to understand how text-technological data structures function in modern computing environments.

Key Features

Focuses on the theoretical foundations of representing natural language texts for computational use.

Covers concrete operations involved in the automatic processing of textual data.

Part of the Studies in Computational Intelligence series, volume 370, by Springer.

Offers an integrated approach to modeling, learning, and processing text-technological structures.

Provides diverse research contributions applicable to many scientific disciplines.

Addresses text as a primary information unit for written communication analysis.

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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