Conferences related to Natural Language Processing

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2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2018 13th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchersin robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior,anthropology, and many other fields.

  • 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    The conference serves as the primary annual meeting for researchers in the field of human-robot interaction. The event will include a main papers track and additional sessions for posters, demos, and exhibits. Additionally, the conference program will include a full day of workshops and tutorials running in parallel.

  • 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    This conference focuses on the interaction between humans and robots.

  • 2015 10th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single -track, highly selective annual conference that showcases the very bestresearch and thinking in human -robot interaction. HRI is inherently interdisciplinary and multidisciplinary,reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificialintelligence, organizational behavior, anthropology, and many other fields.

  • 2014 9th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a highly selective annual conference that showcases the very best research and thinking in human -robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single -track, highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2012 7th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    HRI is a single-track, highly selective annual conference that showcases the very best research and thinking in human-robot interaction. HRI is inherently interdisciplinary and multidisciplinary, reflecting work from researchers in robotics, psychology, cognitive science, HCI, human factors, artificial intelligence, organizational behavior, anthropology, and many other fields.

  • 2011 6th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    Robot companions Lifelike robots Assistive (health & personal care) robotics Remote robots Mixed initiative interaction Multi-modal interaction Long-term interaction with robots Awareness and monitoring of humans Task allocation and coordination Autonomy and trust Robot-team learning User studies of HRI Experiments on HRI collaboration Ethnography and field studies HRI software architectures HRI foundations Metrics for teamwork HRI group dynamics.

  • 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    TOPICS: Robot companions, Lifelike robots, Assistive (health & personal care) robotics, Remote robots, Mixed initiative interaction, Multi-modal interaction, Long-term interaction with robots, Awareness and monitoring of humans, Task allocation and coordination, Autonomy and trust, Robot-team learning, User studies of HRI, Experiments on HRI collaboration, Ethnography and field studies, HRI software architectures

  • 2009 4th ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    * Robot companions * Lifelike robots * Assistive (health & personal care) robotics * Remote robots * Mixed initiative interaction * Multi-modal interaction * Long-term interaction with robots * Awareness and monitoring of humans * Task allocation and coordination * Autonomy and trust * Robot-team learning * User studies of HRI * Experiments on HRI collaboration * Ethnography and field studies * HRI software architectures

  • 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI)

    Robot companions Lifelike robots Assistive (health & personal care) robotics Remote robots Mixed initiative interaction Multi-modal interaction Long-term interaction with robots Awareness and monitoring of humans Task allocation and coordination Autonomy and trust Robot-team learning User studies of HRI Experiments on HRI collaboration Ethnography and field studies HRI software architectures HRI foundations Metrics for teamwork HRI group dynamics Individual vs. group HRI

  • 2007 2nd Annual Conference on Human-Robot Interaction (HRI)


2019 IEEE International Professional Communication Conference (ProComm)

The scope of the conference includes the study, development, improvement, and promotion ofeffective techniques for preparing, organizing, processing, editing, collecting, conserving,teaching, and disseminating any form of technical information by and to individuals and groupsby any method of communication. It also includes technical, scientific, industrial, and otheractivities that contribute to the techniques and products used in this field.


ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

ICASSP is the world’s largest and most comprehensive technical conference focused on signal processing and its applications. The conference will feature world-class presentations by internationally renowned speakers, cutting-edge session topics and provide a fantastic opportunity to network with like-minded professionals from around the world.


2018 41st International Conference on Telecommunications and Signal Processing (TSP)

The TSP 2018 Conference is organized by seventeen universities from Czech Rep., Hungary, Turkey, Taiwan, Japan, Slovak Rep., Spain, Bulgaria, France, Slovenia, Croatia, Greece, and Poland, for academics, researchers, and developers and it serves as a premier annual international forum to promote the exchange of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors from the whole Europe, America, Asia, Australia, and Africa. The international expansion motivates the organizers in their effort to providing a platform for exchanging information and experience to help to improve the level and extent of scientific cooperation between university students, academics, and employees of research centers.

  • 2017 40th International Conference on Telecommunications and Signal Processing (TSP)

    The TSP 2017 Conference is organized by fifteen universities from Czech Republic, Hungary, Turkey, Taiwan, Japan, Slovak Republic, Spain, Bulgaria, France, Slovenia, Croatia, and Poland, for academics, researchers, and developers and it serves as a premier annual international forum to promote the exchange of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors from the whole Europe, America, Asia, Australia, and Africa. The international expansion motivates the organizers in their effort to providing a platform for exchanging information and experience to help to improve the level and extent of scientific cooperation between university students, academics, and employees of research centers.

  • 2016 39th International Conference on Telecommunications and Signal Processing (TSP)

    The 2016 39th International Conference on Telecommunications and Signal Processing (TSP) is organized for academics, researchers, and developers and it serves as a forum to promote the exchange of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors from the whole Europe, America, Asia, Australia, and Africa. The international expansion motivates the organizers in their effort to providing a platform for exchanging information and experience to help to improve the level and extent of scientific cooperation between university students, academics, and employees of research centers.

  • 2015 38th International Conference on Telecommunications and Signal Processing (TSP)

    The 2015 38th International Conference on Telecommunications and Signal Processing (TSP) is organized for academics, researchers, and developers and it serves as a forum to promote the exchange of the latest advances in telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists, developers, and specialists, to meet new colleagues, collect new ideas, and establish new cooperation between research groups from universities, research centers, and private sectors from the whole Europe, America, Asia, Australia, and Africa. The international expansion motivates the organizers in their effort to providing a platform for exchanging information and experience to help to improve the level and extent of scientific cooperation between university students, academics, and employees of research centers.

  • 2013 36th International Conference on Telecommunications and Signal Processing (TSP)

    The TSP 2013 conference is organized for, but not limited to, young academics, researchers and developers from different branches of telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists and developers, to meet new colleagues, collect new ideas and establish new cooperation between research groups. The conference originally started as a Central European initiative but recently we have had participants from Universities and Research Centers from the whole Europe and also from Asia, America and Africa.

  • 2012 35th International Conference on Telecommunications and Signal Processing (TSP)

    The TSP 2012 conference is organized for young academics, researchers and developers from different branches of telecommunication technology and signal processing.

  • 2011 34th International Conference on Telecommunications and Signal Processing (TSP)

    The TSP 2011 conference is organized for, but not limited to, young academics, researchers and developers from different branches of telecommunication technology and signal processing. The aim of the conference is to bring together both novice and experienced scientists and developers, to meet new colleagues, collect new ideas and establish new cooperation between research groups. The conference originally started as a Central European initiative but recently we have had participants from Universities and Research Centers from the whole Europe and also from Asia, America and Africa.


2018 Chinese Control And Decision Conference (CCDC)

Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2017 29th Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2016 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create aforum for scientists, engineers and practitioners throughout the world to present the latestadvancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2015 27th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2014 26th Chinese Control And Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create aforum for scientists, engineers and practitioners throughout the world to present the latestadvancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2013 25th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2012 24th Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2011 23rd Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2010 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies

  • 2009 Chinese Control and Decision Conference (CCDC)

    Chinese Control and Decision Conference is an annual international conference to create a forum for scientists, engineers and practitioners throughout the world to present the latest advancement in Control, Decision, Automation, Robotics and Emerging Technologies.

  • 2008 Chinese Control and Decision Conference (CCDC)


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Periodicals related to Natural Language Processing

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Audio, Speech, and Language Processing, IEEE Transactions on

Speech analysis, synthesis, coding speech recognition, speaker recognition, language modeling, speech production and perception, speech enhancement. In audio, transducers, room acoustics, active sound control, human audition, analysis/synthesis/coding of music, and consumer audio. (8) (IEEE Guide for Authors) The scope for the proposed transactions includes SPEECH PROCESSING - Transmission and storage of Speech signals; speech coding; speech enhancement and noise reduction; ...


Computational Biology and Bioinformatics, IEEE/ACM Transactions on

Specific topics of interest include, but are not limited to, sequence analysis, comparison and alignment methods; motif, gene and signal recognition; molecular evolution; phylogenetics and phylogenomics; determination or prediction of the structure of RNA and Protein in two and three dimensions; DNA twisting and folding; gene expression and gene regulatory networks; deduction of metabolic pathways; micro-array design and analysis; proteomics; ...


Fuzzy Systems, IEEE Transactions on

Theory and application of fuzzy systems with emphasis on engineering systems and scientific applications. (6) (IEEE Guide for Authors) Representative applications areas include:fuzzy estimation, prediction and control; approximate reasoning; intelligent systems design; machine learning; image processing and machine vision;pattern recognition, fuzzy neurocomputing; electronic and photonic implementation; medical computing applications; robotics and motion control; constraint propagation and optimization; civil, chemical and ...


Industrial Informatics, IEEE Transactions on

IEEE Transactions on Industrial Informatics focuses on knowledge-based factory automation as a means to enhance industrial fabrication and manufacturing processes. This embraces a collection of techniques that use information analysis, manipulation, and distribution to achieve higher efficiency, effectiveness, reliability, and/or security within the industrial environment. The scope of the Transaction includes reporting, defining, providing a forum for discourse, and informing ...


Information Forensics and Security, IEEE Transactions on

Research on the fundamental contributions and the mathematics behind information forensics, information seurity, surveillance, and systems applications that incorporate these features.


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Most published Xplore authors for Natural Language Processing

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Xplore Articles related to Natural Language Processing

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The Nursing Profession: Implications for AI and Natural Language Processing

[{u'author_order': 1, u'affiliation': u'Queensland University of Technology, Member, Institute for Health and Biomedical Innovation, Australia, a.barnard@qut.edu.au', u'authorUrl': u'https://ieeexplore.ieee.org/author/37949307700', u'full_name': u'Alan Barnard', u'id': 37949307700}] 2007 International Conference on Natural Language Processing and Knowledge Engineering, 2007

Devices which utilise the assistance of artificial intelligence (AI) such as robotic technology are included increasingly in nursing and health environments. In accordance with these developments this paper will highlight issues for natural language processing that arise from the contexts of nursing practice with specific emphasis on the way nurses think and talk about holistic care, nursing language and the ...


Resource-based Natural Language Processing

[{u'author_order': 1, u'affiliation': u'Computational Linguistics Group, National Institute of Information and Communications Technology, 3-5 Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0289, Japan isahara@nict.go.jp', u'authorUrl': u'https://ieeexplore.ieee.org/author/37283338500', u'full_name': u'Hitoshi Isahara', u'id': 37283338500}] 2007 International Conference on Natural Language Processing and Knowledge Engineering, 2007

Research on natural language processing (NLP) started with so-called rule- based methodology, however, compilation of huge amount of grammar rules and dictionary entries are too difficult to develop practical systems. Then, trend of NLP research shifted to corpus-based, or statistical systems. Thanks to the rapid improvement of computer power and data storage, nowadays we can utilize huge amount of actual ...


On Application of Natural Language Processing in Machine Translation

[{u'author_order': 1, u'full_name': u'Zhaorong Zong'}, {u'author_order': 2, u'full_name': u'Changchun Hong'}] 2018 3rd International Conference on Mechanical, Control and Computer Engineering (ICMCCE), 2018

Natural language processing is the core of machine translation. In the history, its development process is almost the same as machine translation, and the two complement each other. This article compares the natural language processing of statistical corpora with neural machine translation and concludes the natural language processing: Neural machine translation has the advantage of deep learning, which is very ...


Voice controlled home automation system using Natural Language Processing (NLP) and Internet of Things (IoT)

[{u'author_order': 1, u'affiliation': u'Department of Computer Science, Rajalakshmi Institute of Technology, India', u'full_name': u'Paul Jasmin Rani'}, {u'author_order': 2, u'affiliation': u'UG, Department of Computer Science, Rajalakshmi Institute of Technology, India', u'authorUrl': u'https://ieeexplore.ieee.org/author/37085849494', u'full_name': u'Jason Bakthakumar', u'id': 37085849494}, {u'author_order': 3, u'affiliation': u'UG, Department of Computer Science, Rajalakshmi Institute of Technology, India', u'full_name': u'B. Praveen Kumaar'}, {u'author_order': 4, u'affiliation': u'UG, Department of Computer Science, Rajalakshmi Institute of Technology, India', u'full_name': u'U. Praveen Kumaar'}, {u'author_order': 5, u'affiliation': u'UG, Department of Computer Science, Rajalakshmi Institute of Technology, India', u'authorUrl': u'https://ieeexplore.ieee.org/author/37086287299', u'full_name': u'Santhosh Kumar', u'id': 37086287299}] 2017 Third International Conference on Science Technology Engineering & Management (ICONSTEM), 2017

The primary objective of our project is to construct a fully functional voice based Home automation system that uses Internet of Things, Artificial Intelligence and Natural Language Processing (NLP) to provide a cost- effective, efficient way to work together with home appliances. There are many smart home solutions in the market that aim to automate the basic operations of these ...


Research on chinese subjective questions scroing algorithm based on natural language processing

[{u'author_order': 1, u'affiliation': u'Modern Education Technology Center, Guilin University of Technology, China', u'full_name': u'Fanjin Mai'}, {u'author_order': 2, u'affiliation': u'Modern Education Technology Center, Guilin University of Technology, China', u'full_name': u'Xiaoguang Yue'}, {u'author_order': 3, u'affiliation': u'Mechanical and Electronic Engineering College, Taiyuan University of Science and Technology, China', u'full_name': u'Ziqiang Zhao'}] 2010 2nd International Conference on Advanced Computer Control, 2010

Automatic scoring is a help to teachers of giving students exact marks in examination. This article focuses on the method by using natural language processing technology to achieve a viable algorithm. The concepts of the forward maximum matching algorithm and semantic similarity computation and contrary degree calculation are described in this paper. From what has been discussed above, Chinese subjective ...


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IEEE.tv Videos

Computing with Words: Towards an Ultimately Human Centric Computing Paradigm
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IEEE-USA E-Books

  • Learning to Rank for Information Retrieval and Natural Language Processing: Second Edition

    Learning to rank refers to machine learning techniques for training a model in a ranking task. Learning to rank is useful for many applications in information retrieval, natural language processing, and data mining. Intensive studies have been conducted on its problems recently, and significant progress has been made. This lecture gives an introduction to the area including the fundamental problems, major approaches, theories, applications, and future work. The author begins by showing that various ranking problems in information retrieval and natural language processing can be formalized as two basic ranking tasks, namely ranking creation (or simply ranking) and ranking aggregation. In ranking creation, given a request, one wants to generate a ranking list of offerings based on the features derived from the request and the offerings. In ranking aggregation, given a request, as well as a number of ranking lists of offerings, one wants to generate a new ranking list of the offerings. Ranking creation (or ranking) is the major problem in learning to rank. It is usually formalized as a supervised learning task. The author gives detailed explanations on learning for ranking creation and ranking aggregation, including training and testing, evaluation, feature creation, and major approaches. Many methods have been proposed for ranking creation. The methods can be categorized as the pointwise, pairwise, and listwise approaches according to the loss functions they employ. They can also be categorized according to the techniques they employ, such as the SVM based, Boosting based, and Neural Network based approaches. The author also introduces some popular learning to rank methods in details. These include: PRank, OC SVM, McRank, Ranking SVM, IR SVM, GBRank, RankNet, ListNet & ListMLE, AdaRank, SVM MAP, SoftRank, LambdaRank, LambdaMART, Borda Count, Markov Chain, and CRanking. The author explains several example applications of learning to rank including web search, collaborative filtering, definition search, keyphrase extraction, query dependent summarization, and re-ranking in machine translation. A formulation of learning for ranking creation is given in the statistical learning framework. Ongoing and future research directions for learning to rank are also discussed. Table of Contents: Learning to Rank / Learning for Ranking Creation / Learning for Ranking Aggregation / Methods of Learning to Rank / Applications of Learning to Rank / Theory of Learning to Rank / Ongoing and Future Work

  • Linguistic Fundamentals for Natural Language Processing: 100 Essentials from Morphology and Syntax

    Many NLP tasks have at their core a subtask of extracting the dependencies—who did what to whom—from natural language sentences. This task can be understood as the inverse of the problem solved in different ways by diverse human languages, namely, how to indicate the relationship between different parts of a sentence. Understanding how languages solve the problem can be extremely useful in both feature design and error analysis in the application of machine learning to NLP. Likewise, understanding cross-linguistic variation can be important for the design of MT systems and other multilingual applications. The purpose of this book is to present in a succinct and accessible fashion information about the morphological and syntactic structure of human languages that can be useful in creating more linguistically sophisticated, more language-independent, and thus more successful NLP systems. Table of Contents: Acknowledgments / Introduction/motivation / Morphology: Introduction / Morphophonology / Morphosyntax / Syntax: Introduction / Parts of speech / Heads, arguments, and adjuncts / Argument types and grammatical functions / Mismatches between syntactic position and semantic roles / Resources / Bibliography / Author's Biography / General Index / Index of Languages

  • The Sphere of Lexicons and Knowledge

    Located at the intersection of semantics and lexicology, lexical semantics focuses on the meaning of words and their variations. This chapter focuses on the forms of extension of lexical meaning, the paradigmatic relations between words and the main theories concerning lexical meaning. The figurative use of lexical items occurs in different forms. The chapter discusses these forms in detail. Several automatic natural language processing applications use structured lexical resources in the treatment process. Often created in the form of some kind of database, these resources are intended to provide easy access to information related to words, especially their morphology and semantics. Formalisms to represent knowledge were developed to create ontologies. The main difference between an ontology and knowledge is that an ontology is independent of language, it is generic, it can be enriched and it is available in a digital format that is easy to manipulate with a computer.

  • The Sphere of Applications

    This chapter focuses on combining different levels of linguistic knowledge with other sources of knowledge to build applicative natural language processing (NLP) software that is directly usable by humans. It presents the specificities of NLP software regarding their development cycle, architecture and evaluation. Several forms of software architecture have been developed, many of which are intended for the development of commercial applications for information systems. The chapter gives a general introduction to machine translation. After 1975, there was an increase in the need for translation systems by companies. This resurgence in interest was also supported by the development of new computer and electronic tools, such as programming languages and modeling, and the availability of more powerful computers. The systems developed at this time were mainly the most advanced and most sophisticated second‐generation systems. Finally, the chapter presents some closing thoughts on concepts covered in the preceding chapters of this book.

  • Natural Language Processing for Social Media

    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.

  • The Sphere of Discourse and Text

    This chapter addresses the key concepts in the domain of discourse analysis, and reviews the terminology. Discourse analysis focuses on coherence. Discourse analysis pertains to all extra‐sentential phenomena including those observed in texts. The discourse is made of utterances, sentences used in a specific context with a given communicative goal, which have the property of being coherent. The interpretation of an utterance does not only occur through the elements that are explicitly present. This chapter discusses the construction of a tree structure for discourse. This level of analysis can easily be considered the syntax of the discourse. Naturally, every syntactic structure needs a semantic framework for its interpretation and that is where Discourse Representation Theory (DRT) comes in. In modern semantics, a new movement emerged. The focus of this movement is discourse, which it considers to be the unit that must have a truth value, rather than the sentence.

  • The Sphere of Semantics

    Interpretive semantics establishes a clear distinction between aspects of interpretation that are founded on linguistic knowledge and aspects of interpretation that are derived from knowledge about the world. According to this theory, it is this distinction that makes it possible to draw the boundary between semantics and pragmatics. Developed in the mid‐1960s in response to the interpretive semantics of Fodor and Katz, generative semantics stipulates that the semantic component is generative while the syntactic component is interpretive. This chapter presents Rastier's semantic approach and the levels of linguistic description that he identifies in order to clarify his terminology and situate his work within the general context. First‐order logic makes it possible to represent the semantics of natural languages in a more flexible and compact way than propositional logic. Contrary to the logic of propositions, which assumes that the world only contains facts, this logic assumes that the world contains terms, predicates and quantifiers.

  • Introduction to Chinese Natural Language Processing

    This book introduces Chinese language-processing issues and techniques to readers who already have a basic background in natural language processing (NLP). Since the major difference between Chinese and Western languages is at the word level, the book primarily focuses on Chinese morphological analysis and introduces the concept, structure, and interword semantics of Chinese words. The following topics are covered: a general introduction to Chinese NLP; Chinese characters, morphemes, and words and the characteristics of Chinese words that have to be considered in NLP applications; Chinese word segmentation; unknown word detection; word meaning and Chinese linguistic resources; interword semantics based on word collocation and NLP techniques for collocation extraction. Table of Contents: Introduction / Words in Chinese / Challenges in Chinese Morphological Processing / Chinese Word Segmentation / Unknown Word Identification / Word Meaning / Chinese Collocations / Automatic Chinese Collocation Extraction / Appendix / References / Author Biographies

  • Introduction to Arabic Natural Language Processing

    This book provides system developers and researchers in natural language processing and computational linguistics with the necessary background information for working with the Arabic language. The goal is to introduce Arabic linguistic phenomena and review the state-of-the-art in Arabic processing. The book discusses Arabic script, phonology, orthography, morphology, syntax and semantics, with a final chapter on machine translation issues. The chapter sizes correspond more or less to what is linguistically distinctive about Arabic, with morphology getting the lion's share, followed by Arabic script. No previous knowledge of Arabic is needed. This book is designed for computer scientists and linguists alike. The focus of the book is on Modern Standard Arabic; however, notes on practical issues related to Arabic dialects and languages written in the Arabic script are presented in different chapters. Table of Contents: What is "Arabic"? / Arabic Script / Arabic Phonology and Orthography / Arabic Morphology / Computational Morphology Tasks / Arabic Syntax / A Note on Arabic Semantics / A Note on Arabic and Machine Translation

  • Natural Language Processing for Social Media: Second Edition

    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.



Standards related to Natural Language Processing

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