Ontology-Based Interpretation of Natural Language

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Publisher : Springer Nature
ISBN 13 : 3031021541
Total Pages : 158 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Ontology-Based Interpretation of Natural Language by : Philipp Cimiano

Download or read book Ontology-Based Interpretation of Natural Language written by Philipp Cimiano and published by Springer Nature. This book was released on 2022-06-01 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: For humans, understanding a natural language sentence or discourse is so effortless that we hardly ever think about it. For machines, however, the task of interpreting natural language, especially grasping meaning beyond the literal content, has proven extremely difficult and requires a large amount of background knowledge. This book focuses on the interpretation of natural language with respect to specific domain knowledge captured in ontologies. The main contribution is an approach that puts ontologies at the center of the interpretation process. This means that ontologies not only provide a formalization of domain knowledge necessary for interpretation but also support and guide the construction of meaning representations. We start with an introduction to ontologies and demonstrate how linguistic information can be attached to them by means of the ontology lexicon model lemon. These lexica then serve as basis for the automatic generation of grammars, which we use to compositionally construct meaning representations that conform with the vocabulary of an underlying ontology. As a result, the level of representational granularity is not driven by language but by the semantic distinctions made in the underlying ontology and thus by distinctions that are relevant in the context of a particular domain. We highlight some of the challenges involved in the construction of ontology-based meaning representations, and show how ontologies can be exploited for ambiguity resolution and the interpretation of temporal expressions. Finally, we present a question answering system that combines all tools and techniques introduced throughout the book in a real-world application, and sketch how the presented approach can scale to larger, multi-domain scenarios in the context of the Semantic Web. Table of Contents: List of Figures / Preface / Acknowledgments / Introduction / Ontologies / Linguistic Formalisms / Ontology Lexica / Grammar Generation / Putting Everything Together / Ontological Reasoning for Ambiguity Resolution / Temporal Interpretation / Ontology-Based Interpretation for Question Answering / Conclusion / Bibliography / Authors' Biographies

Ontology-Based Interpretation of Natural Language

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Publisher :
ISBN 13 : 9781608459896
Total Pages : 0 pages
Book Rating : 4.4/5 (598 download)

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Book Synopsis Ontology-Based Interpretation of Natural Language by : Philipp Cimiano

Download or read book Ontology-Based Interpretation of Natural Language written by Philipp Cimiano and published by . This book was released on 2014 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: For humans, understanding a natural language sentence or discourse is so effortless that we hardly ever think about it. For machines, however, the task of interpreting natural language, especially grasping meaning beyond the literal content, has proven extremely difficult and requires a large amount of background knowledge. This book focuses on the interpretation of natural language with respect to specific domain knowledge captured in ontologies. The main contribution is an approach that puts ontologies at the center of the interpretation process. This means that ontologies not only provide a formalization of domain knowledge necessary for interpretation but also support and guide the construction of meaning representations. We start with an introduction to ontologies and demonstrate how linguistic information can be attached to them by means of the ontology lexicon model lemon. These lexica then serve as basis for the automatic generation of grammars, which we use to compositionally construct meaning representations that conform with the vocabulary of an underlying ontology. As a result, the level of representational granularity is not driven by language but by the semantic distinctions made in the underlying ontology and thus by distinctions that are relevant in the context of a particular domain. We highlight some of the challenges involved in the construction of ontology-based meaning representations, and show how ontologies can be exploited for ambiguity resolution and the interpretation of temporal expressions. Finally, we present a question answering system that combines all tools and techniques introduced throughout the book in a real-world application, and sketch how the presented approach can scale to larger, multi-domain scenarios in the context of the Semantic Web.

Semantic Similarity from Natural Language and Ontology Analysis

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Publisher : Springer Nature
ISBN 13 : 3031021568
Total Pages : 245 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Semantic Similarity from Natural Language and Ontology Analysis by : Sébastien Harispe

Download or read book Semantic Similarity from Natural Language and Ontology Analysis written by Sébastien Harispe and published by Springer Nature. This book was released on 2022-05-31 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpora analysis and is based on Natural Language Processing techniques and semantic models while the second is based on more or less formal, computer-readable and workable forms of knowledge such as semantic networks, thesauri or ontologies. Semantic measures are widely used today to compare units of language, concepts, instances or even resources indexed by them (e.g., documents, genes). They are central elements of a large variety of Natural Language Processing applications and knowledge-based treatments, and have therefore naturally been subject to intensive and interdisciplinary research efforts during last decades. Beyond a simple inventory and categorization of existing measures, the aim of this monograph is to convey novices as well as researchers of these domains toward a better understanding of semantic similarity estimation and more generally semantic measures. To this end, we propose an in-depth characterization of existing proposals by discussing their features, the assumptions on which they are based and empirical results regarding their performance in particular applications. By answering these questions and by providing a detailed discussion on the foundations of semantic measures, our aim is to give the reader key knowledge required to: (i) select the more relevant methods according to a particular usage context, (ii) understand the challenges offered to this field of study, (iii) distinguish room of improvements for state-of-the-art approaches and (iv) stimulate creativity toward the development of new approaches. In this aim, several definitions, theoretical and practical details, as well as concrete applications are presented.

The Semantic Web

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Publisher : Springer Science & Business Media
ISBN 13 : 3540762973
Total Pages : 998 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis The Semantic Web by : Karl Aberer

Download or read book The Semantic Web written by Karl Aberer and published by Springer Science & Business Media. This book was released on 2007-10-22 with total page 998 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the joint 6th International Semantic Web Conference, ISWC 2007, and the 2nd Asian Semantic Web Conference, ASWC 2007, held in Busan, Korea, in November 2007. The 50 revised full academic papers and 12 revised application papers presented together with 5 Semantic Web Challenge papers and 12 selected doctoral consortium articles were carefully reviewed and selected from a total of 257 submitted papers to the academic track and 29 to the applications track. The papers address all current issues in the field of the semantic Web, ranging from theoretical and foundational aspects to various applied topics such as management of semantic Web data, ontologies, semantic Web architecture, social semantic Web, as well as applications of the semantic Web. Short descriptions of the top five winning applications submitted to the Semantic Web Challenge competition conclude the volume.

Computational Linguistics and Intelligent Text Processing

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Publisher : Springer Science & Business Media
ISBN 13 : 3642121152
Total Pages : 778 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Computational Linguistics and Intelligent Text Processing by : Alexander Gelbukh

Download or read book Computational Linguistics and Intelligent Text Processing written by Alexander Gelbukh and published by Springer Science & Business Media. This book was released on 2010-03-18 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 11th International Conference on Computational Linguistics and Intelligent Text Processing, held in Iaşi, Romania, in March 2010. The 60 paper included in the volume were carefully reviewed and selected from numerous submissions. The book also includes 3 invited papers. The topics covered are: lexical resources, syntax and parsing, word sense disambiguation and named entity recognition, semantics and dialog, humor and emotions, machine translation and multilingualism, information extraction, information retrieval, text categorization and classification, plagiarism detection, text summarization, and speech generation.

Bayesian Analysis in Natural Language Processing

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Publisher : Springer Nature
ISBN 13 : 3031021614
Total Pages : 266 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Bayesian Analysis in Natural Language Processing by : Shay Cohen

Download or read book Bayesian Analysis in Natural Language Processing written by Shay Cohen and published by Springer Nature. This book was released on 2022-11-10 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) went through a profound transformation in the mid-1980s when it shifted to make heavy use of corpora and data-driven techniques to analyze language. Since then, the use of statistical techniques in NLP has evolved in several ways. One such example of evolution took place in the late 1990s or early 2000s, when full-fledged Bayesian machinery was introduced to NLP. This Bayesian approach to NLP has come to accommodate for various shortcomings in the frequentist approach and to enrich it, especially in the unsupervised setting, where statistical learning is done without target prediction examples. We cover the methods and algorithms that are needed to fluently read Bayesian learning papers in NLP and to do research in the area. These methods and algorithms are partially borrowed from both machine learning and statistics and are partially developed "in-house" in NLP. We cover inference techniques such as Markov chain Monte Carlo sampling and variational inference, Bayesian estimation, and nonparametric modeling. We also cover fundamental concepts in Bayesian statistics such as prior distributions, conjugacy, and generative modeling. Finally, we cover some of the fundamental modeling techniques in NLP, such as grammar modeling and their use with Bayesian analysis.

Knowledge Science, Engineering and Management

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Publisher : Springer Science & Business Media
ISBN 13 : 3642104878
Total Pages : 482 pages
Book Rating : 4.6/5 (421 download)

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Book Synopsis Knowledge Science, Engineering and Management by : Dimitris Karagiannis

Download or read book Knowledge Science, Engineering and Management written by Dimitris Karagiannis and published by Springer Science & Business Media. This book was released on 2009-11-17 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Knowledge Science, Engineering and Management, KSEM 2009, held in Vienna, Austria, in November 2009. The 42 revised full papers and 2 discussion panels presented were carefully reviewed and selected from numerous submissions for inclusion in the book. The papers provide new ideas and report state of the art research results in the broad areas of knowledge science, knowledge engineering, and knowledge management.

Linguistic Fundamentals for Natural Language Processing II

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Publisher : Springer Nature
ISBN 13 : 303102172X
Total Pages : 250 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Linguistic Fundamentals for Natural Language Processing II by : Emily M. Bender

Download or read book Linguistic Fundamentals for Natural Language Processing II written by Emily M. Bender and published by Springer Nature. This book was released on 2022-06-01 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Meaning is a fundamental concept in Natural Language Processing (NLP), in the tasks of both Natural Language Understanding (NLU) and Natural Language Generation (NLG). This is because the aims of these fields are to build systems that understand what people mean when they speak or write, and that can produce linguistic strings that successfully express to people the intended content. In order for NLP to scale beyond partial, task-specific solutions, researchers in these fields must be informed by what is known about how humans use language to express and understand communicative intents. The purpose of this book is to present a selection of useful information about semantics and pragmatics, as understood in linguistics, in a way that's accessible to and useful for NLP practitioners with minimal (or even no) prior training in linguistics.

Modern Computational Models of Semantic Discovery in Natural Language

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Publisher : IGI Global
ISBN 13 : 146668691X
Total Pages : 335 pages
Book Rating : 4.4/5 (666 download)

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Book Synopsis Modern Computational Models of Semantic Discovery in Natural Language by : Žižka, Jan

Download or read book Modern Computational Models of Semantic Discovery in Natural Language written by Žižka, Jan and published by IGI Global. This book was released on 2015-07-17 with total page 335 pages. Available in PDF, EPUB and Kindle. Book excerpt: Language—that is, oral or written content that references abstract concepts in subtle ways—is what sets us apart as a species, and in an age defined by such content, language has become both the fuel and the currency of our modern information society. This has posed a vexing new challenge for linguists and engineers working in the field of language-processing: how do we parse and process not just language itself, but language in vast, overwhelming quantities? Modern Computational Models of Semantic Discovery in Natural Language compiles and reviews the most prominent linguistic theories into a single source that serves as an essential reference for future solutions to one of the most important challenges of our age. This comprehensive publication benefits an audience of students and professionals, researchers, and practitioners of linguistics and language discovery. This book includes a comprehensive range of topics and chapters covering digital media, social interaction in online environments, text and data mining, language processing and translation, and contextual documentation, among others.

Embeddings in Natural Language Processing

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Publisher : Morgan & Claypool Publishers
ISBN 13 : 1636390226
Total Pages : 177 pages
Book Rating : 4.6/5 (363 download)

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Book Synopsis Embeddings in Natural Language Processing by : Mohammad Taher Pilehvar

Download or read book Embeddings in Natural Language Processing written by Mohammad Taher Pilehvar and published by Morgan & Claypool Publishers. This book was released on 2020-11-13 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Embeddings have undoubtedly been one of the most influential research areas in Natural Language Processing (NLP). Encoding information into a low-dimensional vector representation, which is easily integrable in modern machine learning models, has played a central role in the development of NLP. Embedding techniques initially focused on words, but the attention soon started to shift to other forms: from graph structures, such as knowledge bases, to other types of textual content, such as sentences and documents. This book provides a high-level synthesis of the main embedding techniques in NLP, in the broad sense. The book starts by explaining conventional word vector space models and word embeddings (e.g., Word2Vec and GloVe) and then moves to other types of embeddings, such as word sense, sentence and document, and graph embeddings. The book also provides an overview of recent developments in contextualized representations (e.g., ELMo and BERT) and explains their potential in NLP. Throughout the book, the reader can find both essential information for understanding a certain topic from scratch and a broad overview of the most successful techniques developed in the literature.

Neural Network Methods for Natural Language Processing

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Publisher : Springer Nature
ISBN 13 : 3031021657
Total Pages : 20 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Neural Network Methods for Natural Language Processing by : Yoav Goldberg

Download or read book Neural Network Methods for Natural Language Processing written by Yoav Goldberg and published by Springer Nature. This book was released on 2022-06-01 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries. The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

Natural Language Processing for Social Media

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Publisher : Morgan & Claypool Publishers
ISBN 13 : 1681736136
Total Pages : 197 pages
Book Rating : 4.6/5 (817 download)

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Book Synopsis Natural Language Processing for Social Media by : Atefeh Farzindar

Download or read book Natural Language Processing for Social Media written by Atefeh Farzindar and published by Morgan & Claypool Publishers. This book was released on 2017-12-15 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Syntax-based Statistical Machine Translation

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Publisher : Springer Nature
ISBN 13 : 3031021649
Total Pages : 190 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Syntax-based Statistical Machine Translation by : Philip Williams

Download or read book Syntax-based Statistical Machine Translation written by Philip Williams and published by Springer Nature. This book was released on 2022-05-31 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique book provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies. While phrase-based models have previously dominated the field, syntax-based approaches have proved a popular alternative, as they elegantly solve many of the shortcomings of phrase-based models. The heart of this book is a detailed introduction to decoding for syntax-based models. The book begins with an overview of synchronous-context free grammar (SCFG) and synchronous tree-substitution grammar (STSG) along with their associated statistical models. It also describes how three popular instantiations (Hiero, SAMT, and GHKM) are learned from parallel corpora. It introduces and details hypergraphs and associated general algorithms, as well as algorithms for decoding with both tree and string input. Special attention is given to efficiency, including search approximations such as beam search and cube pruning, data structures, and parsing algorithms. The book consistently highlights the strengths (and limitations) of syntax-based approaches, including their ability to generalize phrase-based translation units, their modeling of specific linguistic phenomena, and their function of structuring the search space.

Building and Evaluating Domain Ontologies

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Publisher : Logos Verlag Berlin GmbH
ISBN 13 : 3832526579
Total Pages : 213 pages
Book Rating : 4.8/5 (325 download)

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Book Synopsis Building and Evaluating Domain Ontologies by : Gintarė Grigonytė

Download or read book Building and Evaluating Domain Ontologies written by Gintarė Grigonytė and published by Logos Verlag Berlin GmbH. This book was released on 2010 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: An ontology is a knowledge representation structure made up of concepts and their interrelations. It represents shared understanding delineated by some domain. The building of an ontology can be addressed from the perspective of natural language processing. This thesis discusses the validity and theoretical background of knowledge acquisition from natural language. It also presents the theoretical and experimental framework for NLP-driven ontology building and evaluation tasks.

New Trends of Research in Ontologies and Lexical Resources

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Publisher : Springer Science & Business Media
ISBN 13 : 3642317820
Total Pages : 289 pages
Book Rating : 4.6/5 (423 download)

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Book Synopsis New Trends of Research in Ontologies and Lexical Resources by : Alessandro Oltramari

Download or read book New Trends of Research in Ontologies and Lexical Resources written by Alessandro Oltramari and published by Springer Science & Business Media. This book was released on 2013-02-01 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: In order to exchange knowledge, humans need to share a common lexicon of words as well as to access the world models underlying that lexicon. What is a natural process for a human turns out to be an extremely hard task for a machine: computers can’t represent knowledge as effectively as humans do, which hampers, for example, meaning disambiguation and communication. Applied ontologies and NLP have been developed to face these challenges. Integrating ontologies with (possibly multilingual) lexical resources is an essential requirement to make human language understandable by machines, and also to enable interoperability and computability across information systems and, ultimately, in the Web. This book explores recent advances in the integration of ontologies and lexical resources, including questions such as building the required infrastructure (e.g., the Semantic Web) and different formalisms, methods and platforms for eliciting, analyzing and encoding knowledge contents (e.g., multimedia, emotions, events, etc.). The contributors look towards next-generation technologies, shifting the focus from the state of the art to the future of Ontologies and Lexical Resources. This work will be of interest to research scientists, graduate students, and professionals in the fields of knowledge engineering, computational linguistics, and semantic technologies.

Artificial Intelligence in Daily Life

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Publisher : Springer Nature
ISBN 13 : 9811576955
Total Pages : 394 pages
Book Rating : 4.8/5 (115 download)

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Book Synopsis Artificial Intelligence in Daily Life by : Raymond S. T. Lee

Download or read book Artificial Intelligence in Daily Life written by Raymond S. T. Lee and published by Springer Nature. This book was released on 2020-08-22 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given the exponential growth of Artificial Intelligence (AI) over the past few decades, AI and its related applications have become part of daily life in ways that we could never have dreamt of only a century ago. Our routines have been changed beyond measure by robotics and AI, which are now used in a vast array of services. Though AI is still in its infancy, we have already benefited immensely. This book introduces readers to basic Artificial Intelligence concepts, and helps them understand the relationship between AI and daily life. In the interest of clarity, the content is divided into four major parts. Part I (AI Concepts) presents fundamental concepts of and information on AI; while Part II (AI Technology) introduces readers to the five core AI Technologies that provide the building blocks for various AI applications, namely: Machine Learning (ML), Data Mining (DM), Computer Vision (CV), Natural Languages Processing (NLP), and Ontology-based Search Engine (OSE). In turn, Part III (AI Applications) reviews major contemporary applications that are impacting our ways of life, working styles and environment, ranging from intelligent agents and robotics to smart campus and smart city projects. Lastly, Part IV (Beyond AI) addresses related topics that are vital to the future development of AI. It also discusses a number of critical issues, such as AI ethics and privacy, the development of a conscious mind, and autonomous robotics in our daily lives.

Ontology and the Lexicon

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Author :
Publisher : Cambridge University Press
ISBN 13 : 0521886597
Total Pages : 361 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Ontology and the Lexicon by : Chu-ren Huang

Download or read book Ontology and the Lexicon written by Chu-ren Huang and published by Cambridge University Press. This book was released on 2010-04 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: An edited collection focusing on the technology involved in enabling integration between lexical resources and semantic technologies.