Natural Language Processing for Global and Local Business

Natural Language Processing for Global and Local Business

Indexed In: SCOPUS
Release Date: July, 2020|Copyright: © 2021 |Pages: 452
DOI: 10.4018/978-1-7998-4240-8
ISBN13: 9781799842408|ISBN10: 1799842401|EISBN13: 9781799842415
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Description & Coverage
Description:

The concept of natural language processing has become one of the preferred methods to better understand consumers, especially in recent years when digital technologies and research methods have developed exponentially. It has become apparent that when responding to international consumers through multiple platforms and speaking in the same language in which the consumers express themselves, companies are improving their standings within the public sphere.

Natural Language Processing for Global and Local Business provides research exploring the theoretical and practical phenomenon of natural language processing through different languages and platforms in terms of today's conditions. Featuring coverage on a broad range of topics such as computational linguistics, information engineering, and translation technology, this book is ideally designed for IT specialists, academics, researchers, students, and business professionals seeking current research on improving and understanding the consumer experience.

Coverage:

The many academic areas covered in this publication include, but are not limited to:

  • Artificial Intelligence
  • CALL
  • Computational Linguistics
  • Consumer Behavior
  • Digital technology
  • Information Engineering
  • Linguistics
  • Personality Prediction
  • Social Media
  • Translation Technology
Reviews & Statements

Regarding chapter 11, "Quality Assurance in Computer-Assisted Translation in Business Environments":
"The research aims to address the errors that arise in business settings with increased use of computer-assisted translation technology, due to increased tasks, collaborative work, and short deadlines. It focuses on creating a methodological framework for quality assurance analysis, evaluating four QA tools, and justifying the introduction of QA into the CAT process. The research includes building a translation memory, extracting terminology, creating a terminology base, and categorizing errors using a multidimensional quality framework. The level of mistakes is calculated and weights are assigned to errors, penalties are calculated, and quality estimation for translation memory is given. The results show that the process is prone to errors and leads to data-driven decisions for improved quality of output results and efficacy of the translation business process."

– Prof. Ivan Dunder, University of Zagreb, Croatia
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Editor/Author Biographies

Fatih Pinarbasi is a research assistant at Istanbul Medipol University and a PhD student at Yildiz Technical University. His research areas are digital marketing and data mining.

The author was born in Istanbul, Turkiye. She received her BA degree from Istanbul University, Faculty of Letters, English Language
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