Description

Book Synopsis
Text analytics (TA) covers a very wide research area. Its overarching goal is to discover and present knowledge — facts, rules, and relationships — that is otherwise hidden in the textual content. The authors of this book guide us in a quest to attain this knowledge automatically, by applying various machine learning techniques.This book describes recent development in multilingual text analysis. It covers several specific examples of practical TA applications, including their problem statements, theoretical background, and implementation of the proposed solution. The reader can see which preprocessing techniques and text representation models were used, how the evaluation process was designed and implemented, and how these approaches can be adapted to multilingual domains.

Multilingual Text Analysis: Challenges, Models,

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Order before 4pm tomorrow for delivery by Wed 21 Jan 2026.

A Hardback by Marina Litvak, Natalia Vanetik

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    View other formats and editions of Multilingual Text Analysis: Challenges, Models, by Marina Litvak

    Publisher: World Scientific Publishing Co Pte Ltd
    Publication Date: 05/03/2019
    ISBN13: 9789813274877, 978-9813274877
    ISBN10: 9813274875
    Also in:
    Machine learning Programming and scripting languages: general

    Description

    Book Synopsis
    Text analytics (TA) covers a very wide research area. Its overarching goal is to discover and present knowledge — facts, rules, and relationships — that is otherwise hidden in the textual content. The authors of this book guide us in a quest to attain this knowledge automatically, by applying various machine learning techniques.This book describes recent development in multilingual text analysis. It covers several specific examples of practical TA applications, including their problem statements, theoretical background, and implementation of the proposed solution. The reader can see which preprocessing techniques and text representation models were used, how the evaluation process was designed and implemented, and how these approaches can be adapted to multilingual domains.

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