Multilingual Text Analysis: Challenges, Models, And Approaches

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.

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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