Download or read book Natural Language Understanding in a Semantic Web Context written by Caroline Barrière and published by Springer. This book was released on 2016-11-17 with total page 323 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book serves as a starting point for Semantic Web (SW) students and researchers interested in discovering what Natural Language Processing (NLP) has to offer. NLP can effectively help uncover the large portions of data held as unstructured text in natural language, thus augmenting the real content of the Semantic Web in a significant and lasting way. The book covers the basics of NLP, with a focus on Natural Language Understanding (NLU), referring to semantic processing, information extraction and knowledge acquisition, which are seen as the key links between the SW and NLP communities. Major emphasis is placed on mining sentences in search of entities and relations. In the course of this “quest", challenges will be encountered for various text analysis tasks, including part-of-speech tagging, parsing, semantic disambiguation, named entity recognition and relation extraction. Standard algorithms associated with these tasks are presented to provide an understanding of the fundamental concepts. Furthermore, the importance of experimental design and result analysis is emphasized, and accordingly, most chapters include small experiments on corpus data with quantitative and qualitative analysis of the results. This book is divided into four parts. Part I “Searching for Entities in Text” is dedicated to the search for entities in textual data. Next, Part II “Working with Corpora” investigates corpora as valuable resources for NLP work. In turn, Part III “Semantic Grounding and Relatedness” focuses on the process of linking surface forms found in text to entities in resources. Finally, Part IV “Knowledge Acquisition” delves into the world of relations and relation extraction. The book also includes three appendices: “A Look into the Semantic Web” gives a brief overview of the Semantic Web and is intended to bring readers less familiar with the Semantic Web up to speed, so that they too can fully benefit from the material of this book. “NLP Tools and Platforms” provides information about NLP platforms and tools, while “Relation Lists” gathers lists of relations under different categories, showing how relations can be varied and serve different purposes. And finally, the book includes a glossary of over 200 terms commonly used in NLP. The book offers a valuable resource for graduate students specializing in SW technologies and professionals looking for new tools to improve the applicability of SW techniques in everyday life – or, in short, everyone looking to learn about NLP in order to expand his or her horizons. It provides a wealth of information for readers new to both fields, helping them understand the underlying principles and the challenges they may encounter.
Download or read book Natural Language Processing for the Semantic Web written by Diana Maynard and published by Springer Nature. This book was released on 2022-05-31 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces core natural language processing (NLP) technologies to non-experts in an easily accessible way, as a series of building blocks that lead the user to understand key technologies, why they are required, and how to integrate them into Semantic Web applications. Natural language processing and Semantic Web technologies have different, but complementary roles in data management. Combining these two technologies enables structured and unstructured data to merge seamlessly. Semantic Web technologies aim to convert unstructured data to meaningful representations, which benefit enormously from the use of NLP technologies, thereby enabling applications such as connecting text to Linked Open Data, connecting texts to each other, semantic searching, information visualization, and modeling of user behavior in online networks. The first half of this book describes the basic NLP processing tools: tokenization, part-of-speech tagging, and morphological analysis, in addition to the main tools required for an information extraction system (named entity recognition and relation extraction) which build on these components. The second half of the book explains how Semantic Web and NLP technologies can enhance each other, for example via semantic annotation, ontology linking, and population. These chapters also discuss sentiment analysis, a key component in making sense of textual data, and the difficulties of performing NLP on social media, as well as some proposed solutions. The book finishes by investigating some applications of these tools, focusing on semantic search and visualization, modeling user behavior, and an outlook on the future.
Download or read book Natural Language Processing as a Foundation of the Semantic Web written by Yorick Wilks and published by Now Publishers Inc. This book was released on 2009 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Looks at how Natural language Processing underpins the Semantic Web, including its initial construction from unstructured sources like the World Wide Web.
Download or read book Natural Language Processing for the Semantic Web written by Diana Maynard and published by Morgan & Claypool Publishers. This book was released on 2016-12-13 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces core natural language processing (NLP) technologies to non-experts in an easily accessible way, as a series of building blocks that lead the user to understand key technologies, why they are required, and how to integrate them into Semantic Web applications. Natural language processing and Semantic Web technologies have different, but complementary roles in data management. Combining these two technologies enables structured and unstructured data to merge seamlessly. Semantic Web technologies aim to convert unstructured data to meaningful representations, which benefit enormously from the use of NLP technologies, thereby enabling applications such as connecting text to Linked Open Data, connecting texts to each other, semantic searching, information visualization, and modeling of user behavior in online networks. The first half of this book describes the basic NLP processing tools: tokenization, part-of-speech tagging, and morphological analysis, in addition to the main tools required for an information extraction system (named entity recognition and relation extraction) which build on these components. The second half of the book explains how Semantic Web and NLP technologies can enhance each other, for example via semantic annotation, ontology linking, and population. These chapters also discuss sentiment analysis, a key component in making sense of textual data, and the difficulties of performing NLP on social media, as well as some proposed solutions. The book finishes by investigating some applications of these tools, focusing on semantic search and visualization, modeling user behavior, and an outlook on the future.
Download or read book Natural Language Understanding written by James Allen and published by Pearson. This book was released on 1995 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: From a leading authority in artificial intelligence, this book delivers a synthesis of the major modern techniques and the most current research in natural language processing. The approach is unique in its coverage of semantic interpretation and discourse alongside the foundational material in syntactic processing.
Download or read book Handbook of Research on Natural Language Processing and Smart Service Systems written by Pazos-Rangel, Rodolfo Abraham and published by IGI Global. This book was released on 2020-10-02 with total page 554 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural language processing (NLP) is a branch of artificial intelligence that has emerged as a prevalent method of practice for a sizeable amount of companies. NLP enables software to understand human language and process complex data that is generated within businesses. In a competitive market, leading organizations are showing an increased interest in implementing this technology to improve user experience and establish smarter decision-making methods. Research on the application of intelligent analytics is crucial for professionals and companies who wish to gain an edge on the opposition. The Handbook of Research on Natural Language Processing and Smart Service Systems is a collection of innovative research on the integration and development of intelligent software tools and their various applications within professional environments. While highlighting topics including discourse analysis, information retrieval, and advanced dialog systems, this book is ideally designed for developers, practitioners, researchers, managers, engineers, academicians, business professionals, scholars, policymakers, and students seeking current research on the improvement of competitive practices through the use of NLP and smart service systems.
Download or read book Innovations Developments and Applications of Semantic Web and Information Systems written by Lytras, Miltiadis D. and published by IGI Global. This book was released on 2018-01-19 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few years, there has been an increased advancement and evolution in semantic web and information systems in a variety of fields. The integration of these approaches to ontology engineering, sophisticated methods and algorithms for open linked data extraction, and advanced decision-making creates new opportunities for a bright future. Innovations, Developments, and Applications of Semantic Web and Information Systems is a critical scholarly resource that discusses integrated methods of research and analytics in information technology. Featuring coverage on a broad range of topics, such as cognitive computing, artificial intelligence, machine learning, data analysis, and algorithms, this book is geared towards researchers, academicians, and professionals seeking current information on semantic web and information systems.
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
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.
Download or read book Natural Language Understanding written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-07-05 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Natural Language Understanding The field of artificial intelligence known as natural-language processing includes a subfield known as natural-language understanding (NLU), often known as natural-language interpretation (NLI), which deals with the reading comprehension of machines. Understanding natural language is seen as a challenging topic for artificial intelligence. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Natural Language Understanding Chapter 2: Computational Linguistics Chapter 3: Natural Language Processing Chapter 4: Parsing Chapter 5: Question Answering Chapter 6: Semantic Role Labeling Chapter 7: Computational Semantics Chapter 8: Semantic Parsing Chapter 9: Natural-language User Interface Chapter 10: History of Natural Language Processing (II) Answering the public top questions about natural language understanding. (III) Real world examples for the usage of natural language understanding in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of natural language understanding' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of natural language understanding.
Download or read book Speech Language Processing written by Dan Jurafsky and published by Pearson Education India. This book was released on 2000-09 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Representation Learning for Natural Language Processing written by Zhiyuan Liu and published by Springer Nature. This book was released on 2020-07-03 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Natural Language Processing written by Epaminondas Kapetanios and published by CRC Press. This book was released on 2013-11-14 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the semantic aspects of natural language processing and its applications. Topics covered include: measuring word meaning similarity, multi-lingual querying, and parametric theory, named entity recognition, semantics, query language, and the nature of language. The book also emphasizes the portions of mathematics needed to under
Download or read book The Semantic Web Trends and Challenges written by Valentina Presutti and published by Springer. This book was released on 2014-05-09 with total page 926 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 11th Extended Semantic Web Conference, ESWC 2014, held in Anissaras, Crete, Greece France, in May 2014. The 50 revised full papers presented together with three invited talks were carefully reviewed and selected from 204 submissions. They are organized in topical sections on mobile, sensor and semantic streams; services, processes and cloud computing; social web and web science; data management; natural language processing; reasoning; machine learning, linked open data; cognition and semantic web; vocabularies, schemas, ontologies. The book also includes 11 papers presented at the PhD Symposium.
Download or read book Natural Language Processing and Information Systems written by Farid Meziane and published by Springer Science & Business Media. This book was released on 2004-08-13 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 9th International Conference on Applications of Natural Language to Information Systems, NLDB 2004, held in Salford, UK in June 2004. The 29 revised full papers and 13 revised short papers presented were carefully reviewed and selected from 65 submissions. The papers are organized in topical sections on natural language, conversational systems, intelligent querying, linguistic aspects of modeling, information retrieval, natural language text understanding, knowledge bases, knowledge management and content management.
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.
Download or read book Semantic Web Technologies written by Archana Patel and published by CRC Press. This book was released on 2022-10-17 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Semantic web technologies (SWTs) offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. This book provides a roadmap for semantic web technologies (SWTs) and highlights their role in a wide range of domains including cloud computing, Internet of Things, big data, sensor network, and so forth. It also explores the prospects of these technologies including different data interchange formats, query languages, ontologies, Linked Data, and notations. The role of SWTs in ‘epidemic Covid-19’, ‘e-learning platforms and systems’, ‘block chain’, ‘open online courses’, and ‘visual analytics in healthcare’ is described as well. This book: Explores all the critical aspects of semantic web technologies (SWTs) Discusses the impact of SWTs on cloud computing, Internet of Things, big data, and sensor network Offers a comprehensive examination of the emerging research in the areas of SWTs and their related domains Provides a template to develop a wide range of smart and intelligent applications Includes latest applications and examples with real data This book is aimed at researchers and graduate students in computer science, informatics, web technology, cloud computing, and Internet of Things.
