The People’s Web Meets NLP
The People’s Web Meets NLP

Author: Iryna Gurevych

Publisher: Springer Science & Business Media

Published: 2013-04-03

Total Pages: 394

ISBN-13: 3642350852

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Collaboratively Constructed Language Resources (CCLRs) such as Wikipedia, Wiktionary, Linked Open Data, and various resources developed using crowdsourcing techniques such as Games with a Purpose and Mechanical Turk have substantially contributed to the research in natural language processing (NLP). Various NLP tasks utilize such resources to substitute for or supplement conventional lexical semantic resources and linguistically annotated corpora. These resources also provide an extensive body of texts from which valuable knowledge is mined. There are an increasing number of community efforts to link and maintain multiple linguistic resources. This book aims offers comprehensive coverage of CCLR-related topics, including their construction, utilization in NLP tasks, and interlinkage and management. Various Bachelor/Master/Ph.D. programs in natural language processing, computational linguistics, and knowledge discovery can use this book both as the main text and as a supplementary reading. The book also provides a valuable reference guide for researchers and professionals for the above topics.

Recognizing Textual Entailment
Recognizing Textual Entailment

Author: Ido Dagan

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 204

ISBN-13: 3031021517

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In the last few years, a number of NLP researchers have developed and participated in the task of Recognizing Textual Entailment (RTE). This task encapsulates Natural Language Understanding capabilities within a very simple interface: recognizing when the meaning of a text snippet is contained in the meaning of a second piece of text. This simple abstraction of an exceedingly complex problem has broad appeal partly because it can be conceived also as a component in other NLP applications, from Machine Translation to Semantic Search to Information Extraction. It also avoids commitment to any specific meaning representation and reasoning framework, broadening its appeal within the research community. This level of abstraction also facilitates evaluation, a crucial component of any technological advancement program. This book explains the RTE task formulation adopted by the NLP research community, and gives a clear overview of research in this area. It draws out commonalities in this research, detailing the intuitions behind dominant approaches and their theoretical underpinnings. This book has been written with a wide audience in mind, but is intended to inform all readers about the state of the art in this fascinating field, to give a clear understanding of the principles underlying RTE research to date, and to highlight the short- and long-term research goals that will advance this technology.

Semi-Automatic Ontology Development: Processes and Resources
Semi-Automatic Ontology Development: Processes and Resources

Author: Pazienza, Maria Teresa

Publisher: IGI Global

Published: 2012-02-29

Total Pages: 341

ISBN-13: 1466601892

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"This book includes state-of-the-art research results aimed at the automation of ontology development processes and the reuse of external resources becoming a reality, thus being of interest for a wide and diversified community of users"--

Linked Lexical Knowledge Bases
Linked Lexical Knowledge Bases

Author: Iryna Gurevych

Publisher: Springer Nature

Published: 2022-06-01

Total Pages: 124

ISBN-13: 3031021622

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This book conveys the fundamentals of Linked Lexical Knowledge Bases (LLKB) and sheds light on their different aspects from various perspectives, focusing on their construction and use in natural language processing (NLP). It characterizes a wide range of both expert-based and collaboratively constructed lexical knowledge bases. Only basic familiarity with NLP is required and this book has been written for both students and researchers in NLP and related fields who are interested in knowledge-based approaches to language analysis and their applications. Lexical Knowledge Bases (LKBs) are indispensable in many areas of natural language processing, as they encode human knowledge of language in machine readable form, and as such, they are required as a reference when machines attempt to interpret natural language in accordance with human perception. In recent years, numerous research efforts have led to the insight that to make the best use of available knowledge, the orchestrated exploitation of different LKBs is necessary. This allows us to not only extend the range of covered words and senses, but also gives us the opportunity to obtain a richer knowledge representation when a particular meaning of a word is covered in more than one resource. Examples where such an orchestrated usage of LKBs proved beneficial include word sense disambiguation, semantic role labeling, semantic parsing, and text classification. This book presents different kinds of automatic, manual, and collaborative linkings between LKBs. A special chapter is devoted to the linking algorithms employing text-based, graph-based, and joint modeling methods. Following this, it presents a set of higher-level NLP tasks and algorithms, effectively utilizing the knowledge in LLKBs. Among them, you will find advanced methods, e.g., distant supervision, or continuous vector space models of knowledge bases (KB), that have become widely used at the time of this book's writing. Finally, multilingual applications of LLKB's, such as cross-lingual semantic relatedness and computer-aided translation are discussed, as well as tools and interfaces for exploring LLKBs, followed by conclusions and future research directions.

Games with a Purpose (GWAPS)
Games with a Purpose (GWAPS)

Author: Mathieu Lafourcade

Publisher: John Wiley & Sons

Published: 2015-08-10

Total Pages: 158

ISBN-13: 1848218036

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Human brains can be seen as knowledge processors in a distributed system. Each of them can achieve, conscious or not, a small part of a treatment too important to be done by one. These are also "hunter / gatherers" of knowledge. Provided that the number of contributors is large enough, the results are usually better quality than if they were the result of the activity of a single person, even if it is a domain expert. This type of activity is done via online games.

Semantic Web
Semantic Web

Author: Fouad Sabry

Publisher: One Billion Knowledgeable

Published: 2022-07-10

Total Pages: 406

ISBN-13:

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What Is Semantic Web The World Wide Web Consortium is responsible for establishing the standards that will be used in the development of the Semantic Web, which is also referred to as Web 3.0 in certain circles (W3C). Making the data on the Internet understandable by machines is the objective of the Semantic Web. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Semantic Web Chapter 2: DARPA Agent Markup Language Chapter 3: Resource Description Framework Chapter 4: MPEG-7 Chapter 5: Web Ontology Language Chapter 6: RDF Schema Chapter 7: Semantic spectrum Chapter 8: SPARQL Chapter 9: FOAF (ontology) Chapter 10: Semantic wiki Chapter 11: RDFa Chapter 12: Semantic technology Chapter 13: RDF query language Chapter 14: Semantic publishing Chapter 15: Semantic HTML Chapter 16: Semantic Web Stack Chapter 17: Ontology engineering Chapter 18: XHTML+RDFa Chapter 19: Knowledge extraction Chapter 20: Open Semantic Framework Chapter 21: Linguistic Linked Open Data (II) Answering the public top questions about semantic web. (III) Real world examples for the usage of semantic web in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of semantic web' 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 semantic web.

Hard and Soft Computing for Artificial Intelligence, Multimedia and Security
Hard and Soft Computing for Artificial Intelligence, Multimedia and Security

Author: Shin-ya Kobayashi

Publisher: Springer

Published: 2016-10-19

Total Pages: 385

ISBN-13: 331948429X

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This book gathers the proceedings of the 20th International Conference on Advanced Computer Systems 2016, held in Międzyzdroje (Poland) on October 19–21, 2016. Addressing topics that include artificial intelligence (AI), software technologies, multimedia systems, IT security and design of information systems, the main purpose of the conference and the book is to create an opportunity to exchange significant insights on this area between science and business. In particular, this expertise concerns the use of hard and soft computational methods for artificial intelligence, image and data processing, and finally, the design of information and security systems. The book contains a collection of carefully selected, peer-reviewed papers, combining high-quality original unpublished research, case studies, and implementation experiences.

Cases on Open-Linked Data and Semantic Web Applications
Cases on Open-Linked Data and Semantic Web Applications

Author: Ordóñez de Pablos, Patricia

Publisher: IGI Global

Published: 2013-01-31

Total Pages: 304

ISBN-13: 1466628286

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With the purpose of building upon standard web technologies, open linked data serves as a useful way to connect previously unrelated data and to publish structured data on the web. The application of these elements leads to the creation of data commons called semantic web. Cases on Open-Linked Data and Semantic Web Applications brings together new theories, research findings and case studies which cover the recent developments and approaches towards applied open linked data and semantic web in the context of information systems. By enhancing the understanding of open linked data in business, science and information technologies, this reference source aims to be useful for academics, researchers, and practitioners.

Graph-Powered Machine Learning
Graph-Powered Machine Learning

Author: Alessandro Negro

Publisher: Simon and Schuster

Published: 2021-10-05

Total Pages: 494

ISBN-13: 163835393X

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Upgrade your machine learning models with graph-based algorithms, the perfect structure for complex and interlinked data. Summary In Graph-Powered Machine Learning, you will learn: The lifecycle of a machine learning project Graphs in big data platforms Data source modeling using graphs Graph-based natural language processing, recommendations, and fraud detection techniques Graph algorithms Working with Neo4J Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You’ll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you optimize with best design practices. Author Alessandro Negro’s extensive experience shines through in every chapter, as you learn from examples and concrete scenarios based on his work with real clients! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Identifying relationships is the foundation of machine learning. By recognizing and analyzing the connections in your data, graph-centric algorithms like K-nearest neighbor or PageRank radically improve the effectiveness of ML applications. Graph-based machine learning techniques offer a powerful new perspective for machine learning in social networking, fraud detection, natural language processing, and recommendation systems. About the book Graph-Powered Machine Learning teaches you how to exploit the natural relationships in structured and unstructured datasets using graph-oriented machine learning algorithms and tools. In this authoritative book, you’ll master the architectures and design practices of graphs, and avoid common pitfalls. Author Alessandro Negro explores examples from real-world applications that connect GraphML concepts to real world tasks. What's inside Graphs in big data platforms Recommendations, natural language processing, fraud detection Graph algorithms Working with the Neo4J graph database About the reader For readers comfortable with machine learning basics. About the author Alessandro Negro is Chief Scientist at GraphAware. He has been a speaker at many conferences, and holds a PhD in Computer Science. Table of Contents PART 1 INTRODUCTION 1 Machine learning and graphs: An introduction 2 Graph data engineering 3 Graphs in machine learning applications PART 2 RECOMMENDATIONS 4 Content-based recommendations 5 Collaborative filtering 6 Session-based recommendations 7 Context-aware and hybrid recommendations PART 3 FIGHTING FRAUD 8 Basic approaches to graph-powered fraud detection 9 Proximity-based algorithms 10 Social network analysis against fraud PART 4 TAMING TEXT WITH GRAPHS 11 Graph-based natural language processing 12 Knowledge graphs

Human Language Technology Challenges for Computer Science and Linguistics
Human Language Technology Challenges for Computer Science and Linguistics

Author: Zygmunt Vetulani

Publisher: Springer

Published: 2014-07-25

Total Pages: 552

ISBN-13: 3319089587

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This book constitutes the refereed proceedings of the 5th Language and Technology Conference: Challenges for Computer Science and Linguistics, LTC 2011, held in Poznan, Poland, in November 2011. The 44 revised and in many cases substantially extended papers presented in this volume were carefully reviewed and selected from 111 submissions. The focus of the papers is on the following topics: speech, parsing, computational semantics, text analysis, text annotation, language resources: general issues, language resources: ontologies and Wordnets and machine translation.