Knowledge And Learning In Natural Language

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Knowledge And Learning In Natural Language

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Author : Charles D. Yang
language : en
Publisher: OUP Oxford
Release Date : 2002

Knowledge And Learning In Natural Language written by Charles D. Yang and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Language Arts & Disciplines categories.

This book presents a new theory of how children acquire language and discusses its implications for a wide range of topics. It explores the roles of innateness and experience in language acquisition, provides further evidence for the theory of Universal Grammar, and shows how linguistic development in children is a driving force behind language shifts and changes.Charles Yang surveys a wide range of errors in children's language and identifies overlooked patterns. He combines these with work in biological evolution in order to develop a model of language acquisition by which to understand the interaction between children's internal linguistic knowledge and their external linguistic experience. He then presents evidence from his own and others' research in the acquisition of syntax and morphology and data from historical language change to test its validity. The model is the first to make quantitative and cross-linguistic predictions about child language. It may also be deployed as a predictive model of language change which, when the evidence is available, could explain why grammars change in a particular direction at a particular time.Knowledge and Learning in Natural Language is a pioneering work at the centre of current concerns in linguistics and cognitive science. It will interest all those concerned to understand and explain language acquisition, Universal Grammar, and language change.

Representation Learning For Natural Language Processing

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Author : Zhiyuan Liu
language : en
Publisher: Springer Nature
Release Date : 2020-07-03

Representation Learning For Natural Language Processing written by Zhiyuan Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-03 with Computers categories.

This open access book provides an overview of the recent advances in representation learning theory, algorithms and applications for natural language processing (NLP). It is divided into three parts. Part I presents the representation learning techniques for multiple language entries, including words, phrases, sentences and documents. Part II then introduces the representation techniques for those objects that are closely related to NLP, including entity-based world knowledge, sememe-based linguistic knowledge, networks, and cross-modal entries. Lastly, Part III provides open resource tools for representation learning techniques, and discusses the remaining challenges and future research directions. The theories and algorithms of representation learning presented can also benefit other related domains such as machine learning, social network analysis, semantic Web, information retrieval, data mining and computational biology. This book is intended for advanced undergraduate and graduate students, post-doctoral fellows, researchers, lecturers, and industrial engineers, as well as anyone interested in representation learning and natural language processing.

Advances In Natural Computation Fuzzy Systems And Knowledge Discovery

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Author : Yong Liu
language : en
Publisher: Springer Nature
Release Date : 2019-11-06

Advances In Natural Computation Fuzzy Systems And Knowledge Discovery written by Yong Liu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-06 with Technology & Engineering categories.

This book discusses the recent advances in natural computation, fuzzy systems and knowledge discovery. Presenting selected, peer-reviewed papers from the 15th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD 2019), held in Kunming, China, from 20 to 22 July 2019, it is a useful resource for researchers, including professors and graduate students, as well as R&D staff in industry.

Knowledge Engineering For Modern Information Systems

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Author : Anand Sharma
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-01-19

Knowledge Engineering For Modern Information Systems written by Anand Sharma and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-19 with Computers categories.

Knowledge Engineering (KE) is a field within artificial intelligence that develops knowledgebased systems. KE is the process of imitating how a human expert in a specific domain would act and take decisions. It contains large amounts of knowledge, like metadata and information about a data object that describes characteristics such as content, quality, and format, structure and processes. Such systems are computer programs that are the basis of how a decision is made or a conclusion is reached. It is having all the rules and reasoning mechanisms to provide solutions to real-world problems. This book presents an extensive collection of the recent findings and innovative research in the information system and KE domain. Highlighting the challenges and difficulties in implementing these approaches, this book is a critical reference source for academicians, professionals, engineers, technology designers, analysts, undergraduate and postgraduate students in computing science and related disciplines such as Information systems, Knowledge Engineering, Intelligent Systems, Artifi cial Intelligence, Cognitive Neuro - science, and Robotics. In addition, anyone who is interested or involved in sophisticated information systems and knowledge engineering developments will find this book a valuable source of ideas and guidance.

Rough Sets And Knowledge Technology

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Author : Peng Wen
language : en
Publisher: Springer
Release Date : 2009-07-01

Rough Sets And Knowledge Technology written by Peng Wen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-01 with Mathematics categories.

This book constitutes the refereed proceedings of the Fourth International Conference on Rough Sets and Knowledge Technology, RSKT 2009, held in Gold Coast, Australia, in July 2009. The 85 revised full papers papers presented together with 3 keynote papers and 2 special sessions were carefully reviewed and selected from 229 submissions. The papers are organized in topical sections on rough sets and computing, rough sets and data reduction, data mining and knowledge discovery, granular computing and cognitive computing, fuzzy sets and computing, knowledge technology and intelligent systems, computational intelligence and applications, image processing and understanding, and formal concept analysis.

A Course In Natural Language Processing

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Author : Yannis Haralambous
language : en
Publisher: Springer
Release Date : 2024-01-31

A Course In Natural Language Processing written by Yannis Haralambous and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-31 with Computers categories.

Natural Language Processing is the branch of Artificial Intelligence involving language, be it in spoken or written modality. Teaching Natural Language Processing (NLP) is difficult because of its inherent connections with other disciplines, such as Linguistics, Cognitive Science, Knowledge Representation, Machine Learning, Data Science, and its latest avatar: Deep Learning. Most introductory NLP books favor one of these disciplines at the expense of others. Based on a course on Natural Language Processing taught by the author at IMT Atlantique for over a decade, this textbook considers three points of view corresponding to three different disciplines, while granting equal importance to each of them. As such, the book provides a thorough introduction to the topic following three main threads: the fundamental notions of Linguistics, symbolic Artificial Intelligence methods (based on knowledge representation languages), and statistical methods (involving both legacy machine learning and deep learning tools). Complementary to this introductory text is teaching material, such as exercises and labs with hints and expected results. Complete solutions with Python code are provided for educators on the SpringerLink webpage of the book. This material can serve for classes given to undergraduate and graduate students, or for researchers, instructors, and professionals in computer science or linguistics who wish to acquire or improve their knowledge in the field. The book is suitable and warmly recommended for self-study.

Deep Learning In Natural Language Processing

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Author : Li Deng
language : en
Publisher: Springer
Release Date : 2018-05-23

Deep Learning In Natural Language Processing written by Li Deng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-23 with Computers categories.

In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.

Advances In Knowledge Discovery And Data Mining

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Author : Dinh Phung
language : en
Publisher: Springer
Release Date : 2018-06-19

Advances In Knowledge Discovery And Data Mining written by Dinh Phung and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-19 with Computers categories.

This three-volume set, LNAI 10937, 10938, and 10939, constitutes the thoroughly refereed proceedings of the 22nd Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2018, held in Melbourne, VIC, Australia, in June 2018. The 164 full papers were carefully reviewed and selected from 592 submissions. The volumes present papers focusing on new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications.

Data Knowledge Engineering Volume 48 Issue 1

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Author :
language : en
Publisher:
Release Date : 2004

Data Knowledge Engineering Volume 48 Issue 1 written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.

Advances In Knowledge Discovery And Data Mining

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Author : Qiang Yang
language : en
Publisher: Springer
Release Date : 2019-04-03

Advances In Knowledge Discovery And Data Mining written by Qiang Yang and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-03 with Computers categories.

The three-volume set LNAI 11439, 11440, and 11441 constitutes the thoroughly refereed proceedings of the 23rd Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2019, held in Macau, China, in April 2019. The 137 full papers presented were carefully reviewed and selected from 542 submissions. The papers present new ideas, original research results, and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems, and the emerging applications. They are organized in the following topical sections: classification and supervised learning; text and opinion mining; spatio-temporal and stream data mining; factor and tensor analysis; healthcare, bioinformatics and related topics; clustering and anomaly detection; deep learning models and applications; sequential pattern mining; weakly supervised learning; recommender system; social network and graph mining; data pre-processing and featureselection; representation learning and embedding; mining unstructured and semi-structured data; behavioral data mining; visual data mining; and knowledge graph and interpretable data mining.