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Author: Szahel Kumke
Publisher: GRIN Verlag
ISBN: 3346485277
Category : Foreign Language Study
Languages : en
Pages : 20
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Book Description
Academic Paper from the year 2019 in the subject English Language and Literature Studies - Culture and Applied Geography, grade: 1,3, University of Kassel, language: English, abstract: What is math about? Basically spoken, it is about uniting separate parts and bringing together something new. To understand and to read the new creation, it is important to understand the meaning of each part to create further meaning of the whole. Where is the difference to language? To properly understand a language it is important to split it into smaller units and to understand the meaning of each unit it is necessary and helpful to understand the whole language. The mathematical formula is 1+1= language. Firstly, this seems to be confusing but lately, logical. Language does consist of smaller units which, once brought together, build up to a new system, a whole language. To understand a language it is therefore indispensable to understand logical connections but it is not necessary to be a math genius. Today’s most striking field of linguistic, Natural Language Processing (NLP), combines the ability to think logically and to analyse language in an encompassing manner. The aim of this paper is to give a brief introduction on what is Natural Language Processing (NLP) and further, to define several challenges NLP has to face due to online data bias. The challenges which concern the field of technology as well as they influence the social impact form a work frame for the overlaying field of ethical challenges in online data which are going to be displayed in this paper. Not only existing challenges but also future solutions will be a subject of discussion.
Author: Szahel Kumke
Publisher: GRIN Verlag
ISBN: 3346485277
Category : Foreign Language Study
Languages : en
Pages : 20
Get Book Here
Book Description
Academic Paper from the year 2019 in the subject English Language and Literature Studies - Culture and Applied Geography, grade: 1,3, University of Kassel, language: English, abstract: What is math about? Basically spoken, it is about uniting separate parts and bringing together something new. To understand and to read the new creation, it is important to understand the meaning of each part to create further meaning of the whole. Where is the difference to language? To properly understand a language it is important to split it into smaller units and to understand the meaning of each unit it is necessary and helpful to understand the whole language. The mathematical formula is 1+1= language. Firstly, this seems to be confusing but lately, logical. Language does consist of smaller units which, once brought together, build up to a new system, a whole language. To understand a language it is therefore indispensable to understand logical connections but it is not necessary to be a math genius. Today’s most striking field of linguistic, Natural Language Processing (NLP), combines the ability to think logically and to analyse language in an encompassing manner. The aim of this paper is to give a brief introduction on what is Natural Language Processing (NLP) and further, to define several challenges NLP has to face due to online data bias. The challenges which concern the field of technology as well as they influence the social impact form a work frame for the overlaying field of ethical challenges in online data which are going to be displayed in this paper. Not only existing challenges but also future solutions will be a subject of discussion.
Author: Amandalynne Grace Jangmi Paullada
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
Natural language processing (NLP) technologies have transformed how people access information and communicate with one another. It has thus become critical to take stock of the social impact of natural language processing technologies. In this thesis, I review practices at different stages of development for NLP systems and examine some of the issues that arise in turn, considering the social and political contexts that shape how systems are developed and deployed. This thesis contributes three case studies of natural language processing technologies which exemplify many of the key issues in data collection practices and real-world system usage. The first two case studies situate computational models of text and machine translation in the complex social and political contexts that have informed the development of these applications. The third case study involves a reflection on original work in building and evaluating a system for representing biomedical relationships learned from text. In addition to the findings from these case studies, I contribute a practice-based framework for reflecting on factors that influence social impact at various stages of NLP system development.
Author: Anna Atefeh Farzindar
Publisher: Morgan & Claypool Publishers
ISBN: 1681738120
Category : Computers
Languages : en
Pages : 221
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Book Description
In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms that extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. This book will discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts, and it shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, and business intelligence. The book further covers the existing evaluation metrics for NLP and social media applications and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF). In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data.
Author: Atefeh Farzindar
Publisher: Morgan & Claypool Publishers
ISBN: 1681736136
Category : Computers
Languages : en
Pages : 197
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Book Description
In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, healthcare, business intelligence, industry, marketing, and security and defence. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, virtual reality, and social networking. In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.
Author: Madeleine Bates
Publisher: Cambridge University Press
ISBN: 9780521410151
Category : Language Arts & Disciplines
Languages : en
Pages : 312
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Book Description
Though natural language processing has come far in the past twenty years, the technology has not achieved a major impact on society. Is this because of some fundamental limitation that cannot be overcome? Or because there has not been enough time to refine and apply theoretical work already done? Editors Madeleine Bates and Ralph Weischedel believe it is neither; they feel that several critical issues have never been adequately addressed in either theoretical or applied work, and they have invited capable researchers in the field to do that in Challenges in Natural Language Processing.
Author: Brojo Kishore Mishra
Publisher: CRC Press
ISBN: 1000711315
Category : Science
Languages : en
Pages : 297
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Book Description
This volume focuses on natural language processing, artificial intelligence, and allied areas. Natural language processing enables communication between people and computers and automatic translation to facilitate easy interaction with others around the world. This book discusses theoretical work and advanced applications, approaches, and techniques for computational models of information and how it is presented by language (artificial, human, or natural) in other ways. It looks at intelligent natural language processing and related models of thought, mental states, reasoning, and other cognitive processes. It explores the difficult problems and challenges related to partiality, underspecification, and context-dependency, which are signature features of information in nature and natural languages. Key features: Addresses the functional frameworks and workflow that are trending in NLP and AI Looks at the latest technologies and the major challenges, issues, and advances in NLP and AI Explores an intelligent field monitoring and automated system through AI with NLP and its implications for the real world Discusses data acquisition and presents a real-time case study with illustrations related to data-intensive technologies in AI and NLP.
Author: Atefeh Farzindar
Publisher: Springer Nature
ISBN: 3031021576
Category : Computers
Languages : en
Pages : 158
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Book Description
In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on Natural Language Processing (NLP) tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, business intelligence, industry, marketing, and security and defense. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, and social networking.
Author: Atefeh Farzindar
Publisher: Springer Nature
ISBN: 3031021673
Category : Computers
Languages : en
Pages : 188
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Book Description
In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms which extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. We discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts (big data), and shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, healthcare, business intelligence, industry, marketing, and security and defence. We review the existing evaluation metrics for NLP and social media applications, and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks) or by the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC). In the concluding chapter, we discuss the importance of this dynamic discipline and its great potential for NLP in the coming decade, in the context of changes in mobile technology, cloud computing, virtual reality, and social networking. In this second edition, we have added information about recent progress in the tasks and applications presented in the first edition. We discuss new methods and their results. The number of research projects and publications that use social media data is constantly increasing due to continuously growing amounts of social media data and the need to automatically process them. We have added 85 new references to the more than 300 references from the first edition. Besides updating each section, we have added a new application (digital marketing) to the section on media monitoring and we have augmented the section on healthcare applications with an extended discussion of recent research on detecting signs of mental illness from social media.
Author: Hua Xu
Publisher: Springer Nature
ISBN: 3031558650
Category :
Languages : en
Pages : 449
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Book Description
Author: Satya Ranjan Dash
Publisher: CRC Press
ISBN: 1000624684
Category : Computers
Languages : en
Pages : 261
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Book Description
Natural Language Processing In Healthcare: A Special Focus on Low Resource Languages covers the theoretical and practical aspects as well as ethical and social implications of NLP in healthcare. It showcases the latest research and developments contributing to the rising awareness and importance of maintaining linguistic diversity. The book goes on to present current advances and scenarios based on solutions in healthcare and low resource languages and identifies the major challenges and opportunities that will impact NLP in clinical practice and health studies.
