Knowledge Graphs And Language Technology
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| Author | : Marieke van Erp |
| Publisher | : Springer |
| Total Pages | : 147 |
| Release | : 2017-10-28 |
| Genre | : Computers |
| ISBN | : 3319687239 |
This book constitutes the combined refereed proceedings of ISWC Satellite Wor shops KEKIand NLP&DBpedia 2016 which were held in conjunction with ISWC 2016 in Kobe, Japan, inOctober 2016. The 9 papers presented were carefully selected and reviewed from 20submissions. They focus on the use of linguistic linked open data, the linguistic aspectsof DBpedia, the improvement of of DBpedia through NLP applications, on increasing theNLP applications through integrating knowledge from DPpedia.
| Author | : Aidan Hogan |
| Publisher | : Morgan & Claypool Publishers |
| Total Pages | : 257 |
| Release | : 2021-11-08 |
| Genre | : Computers |
| ISBN | : 1636392369 |
This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.
| Author | : Mayank Kejriwal |
| Publisher | : MIT Press |
| Total Pages | : 559 |
| Release | : 2021-03-30 |
| Genre | : Computers |
| ISBN | : 0262045095 |
A rigorous and comprehensive textbook covering the major approaches to knowledge graphs, an active and interdisciplinary area within artificial intelligence. The field of knowledge graphs, which allows us to model, process, and derive insights from complex real-world data, has emerged as an active and interdisciplinary area of artificial intelligence over the last decade, drawing on such fields as natural language processing, data mining, and the semantic web. Current projects involve predicting cyberattacks, recommending products, and even gleaning insights from thousands of papers on COVID-19. This textbook offers rigorous and comprehensive coverage of the field. It focuses systematically on the major approaches, both those that have stood the test of time and the latest deep learning methods.
| Author | : Juan Sequeda |
| Publisher | : Springer Nature |
| Total Pages | : 142 |
| Release | : 2022-05-31 |
| Genre | : Computers |
| ISBN | : 3031019164 |
This book is a guide to designing and building knowledge graphs from enterprise relational databases in practice.\ It presents a principled framework centered on mapping patterns to connect relational databases with knowledge graphs, the roles within an organization responsible for the knowledge graph, and the process that combines data and people. The content of this book is applicable to knowledge graphs being built either with property graph or RDF graph technologies. Knowledge graphs are fulfilling the vision of creating intelligent systems that integrate knowledge and data at large scale. Tech giants have adopted knowledge graphs for the foundation of next-generation enterprise data and metadata management, search, recommendation, analytics, intelligent agents, and more. We are now observing an increasing number of enterprises that seek to adopt knowledge graphs to develop a competitive edge. In order for enterprises to design and build knowledge graphs, they need to understand the critical data stored in relational databases. How can enterprises successfully adopt knowledge graphs to integrate data and knowledge, without boiling the ocean? This book provides the answers.
| Author | : Dieter Fensel |
| Publisher | : Springer Nature |
| Total Pages | : 148 |
| Release | : 2020-01-31 |
| Genre | : Computers |
| ISBN | : 3030374394 |
This book describes methods and tools that empower information providers to build and maintain knowledge graphs, including those for manual, semi-automatic, and automatic construction; implementation; and validation and verification of semantic annotations and their integration into knowledge graphs. It also presents lifecycle-based approaches for semi-automatic and automatic curation of these graphs, such as approaches for assessment, error correction, and enrichment of knowledge graphs with other static and dynamic resources. Chapter 1 defines knowledge graphs, focusing on the impact of various approaches rather than mathematical precision. Chapter 2 details how knowledge graphs are built, implemented, maintained, and deployed. Chapter 3 then introduces relevant application layers that can be built on top of such knowledge graphs, and explains how inference can be used to define views on such graphs, making it a useful resource for open and service-oriented dialog systems. Chapter 4 discusses applications of knowledge graph technologies for e-tourism and use cases for other verticals. Lastly, Chapter 5 provides a summary and sketches directions for future work. The additional appendix introduces an abstract syntax and semantics for domain specifications that are used to adapt schema.org to specific domains and tasks. To illustrate the practical use of the approaches presented, the book discusses several pilots with a focus on conversational interfaces, describing how to exploit knowledge graphs for e-marketing and e-commerce. It is intended for advanced professionals and researchers requiring a brief introduction to knowledge graphs and their implementation.
| Author | : Valentina Janev |
| Publisher | : Springer Nature |
| Total Pages | : 212 |
| Release | : 2020-07-15 |
| Genre | : Computers |
| ISBN | : 3030531996 |
This open access book is part of the LAMBDA Project (Learning, Applying, Multiplying Big Data Analytics), funded by the European Union, GA No. 809965. Data Analytics involves applying algorithmic processes to derive insights. Nowadays it is used in many industries to allow organizations and companies to make better decisions as well as to verify or disprove existing theories or models. The term data analytics is often used interchangeably with intelligence, statistics, reasoning, data mining, knowledge discovery, and others. The goal of this book is to introduce some of the definitions, methods, tools, frameworks, and solutions for big data processing, starting from the process of information extraction and knowledge representation, via knowledge processing and analytics to visualization, sense-making, and practical applications. Each chapter in this book addresses some pertinent aspect of the data processing chain, with a specific focus on understanding Enterprise Knowledge Graphs, Semantic Big Data Architectures, and Smart Data Analytics solutions. This book is addressed to graduate students from technical disciplines, to professional audiences following continuous education short courses, and to researchers from diverse areas following self-study courses. Basic skills in computer science, mathematics, and statistics are required.
| Author | : L.-A. Kaffee |
| Publisher | : IOS Press |
| Total Pages | : 218 |
| Release | : 2023-11-14 |
| Genre | : Computers |
| ISBN | : 1643684558 |
Content on the web is predominantly written in English, making it inaccessible to those who only speak other languages. Knowledge graphs can store multilingual information, facilitate the creation of multilingual applications, and make content accessible to multiple language communities. This book, Multilinguality in Knowledge Graphs, presents studies which assess and improve the state of labels and languages in knowledge graphs and the application of multilingual information. The author proposes ways of using multilingual knowledge graphs to reduce the gaps in coverage between languages, and the book explores the current state of language distribution in knowledge graphs by developing a framework based on existing standards, frameworks, and guidelines to measure label and language distribution in knowledge graphs. Applying this framework to a dataset representing the web of data, and to Wikidata, both a lack of labeling on the web and a bias towards a small set of languages were found. The book explores how a knowledge of labels and languages can be used in the domain of answering questions, and demonstrates how the framework can be applied to the task of ranking and selecting knowledge graphs for a set of user questions. Transliteration and translation of knowledge graph labels and aliases are also covered, as is the automatic classification of labels into one or the other to train a model for each task. The book provides a wide range of information on working with data and knowledge graphs in less-resourced languages.
| Author | : Maribel Acosta |
| Publisher | : Springer Nature |
| Total Pages | : 400 |
| Release | : 2019-11-04 |
| Genre | : Computers |
| ISBN | : 3030332209 |
This open access book constitutes the refereed proceedings of the 15th International Conference on Semantic Systems, SEMANTiCS 2019, held in Karlsruhe, Germany, in September 2019. The 20 full papers and 8 short papers presented in this volume were carefully reviewed and selected from 88 submissions. They cover topics such as: web semantics and linked (open) data; machine learning and deep learning techniques; semantic information management and knowledge integration; terminology, thesaurus and ontology management; data mining and knowledge discovery; semantics in blockchain and distributed ledger technologies.
| Author | : Radek Silhavy |
| Publisher | : Springer Nature |
| Total Pages | : 1073 |
| Release | : 2021-11-16 |
| Genre | : Technology & Engineering |
| ISBN | : 3030903214 |
This book constitutes the second part of refereed proceedings of the 5th Computational Methods in Systems and Software 2021 (CoMeSySo 2021) proceedings. The real-world problems related to data science and algorithm design related to systems and software engineering are presented in this papers. Furthermore, the basic research’ papers that describe novel approaches in the data science, algorithm design and in systems and software engineering are included. The CoMeSySo 2021 conference is breaking the barriers, being held online. CoMeSySo 2021 intends to provide an international forum for the discussion of the latest high-quality research results
| Author | : UMUTCAN. FENSEL SERLES (DIETER.) |
| Publisher | : Springer Nature |
| Total Pages | : 440 |
| Release | : 2024 |
| Genre | : Electronic books |
| ISBN | : 3031452569 |
This textbook introduces the theoretical foundations of technologies essential for knowledge graphs. It also covers practical examples, applications and tools. Knowledge graphs are the most recent answer to the challenge of providing explicit knowledge about entities and their relationships by potentially integrating billions of facts from heterogeneous sources. The book is structured in four parts. For a start, Part I lays down the overall context of knowledge graph technology. Part II “Knowledge Representation” then provides a deep understanding of semantics as the technical core of knowledge graph technology. Semantics is covered from different perspectives, such as conceptual, epistemological and logical. Next, Part III “Knowledge Modelling” focuses on the building process of knowledge graphs. The book focuses on the phases of knowledge generation, knowledge hosting, knowledge assessment, knowledge cleaning, knowledge enrichment, and knowledge deployment to cover a complete life cycle for this process. Finally, Part IV (simply called “Applications”) presents various application areas in detail with concrete application examples as well as an outlook on additional trends that will emphasize the need for knowledge graphs even stronger. This textbook is intended for graduate courses covering knowledge graphs. Besides students in knowledge graph, Semantic Web, database, or information retrieval classes, also advanced software developers for Web applications or tools for Web data management will learn about the foundations and appropriate methods.
