Knowledge Graphs For Multilingual Language Translation And Generation
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Knowledge Graphs For Multilingual Language Translation And Generation
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Author : Diego Campos Moussallem
language : en
Publisher:
Release Date : 2020
Knowledge Graphs For Multilingual Language Translation And Generation written by Diego Campos Moussallem and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Multilinguality In Knowledge Graphs
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Author : L.-A. Kaffee
language : en
Publisher: IOS Press
Release Date : 2023-11-14
Multilinguality In Knowledge Graphs written by L.-A. Kaffee and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-14 with Computers categories.
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.
Knowledge Graphs Semantics Machine Learning And Languages
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Author : M. Acosta
language : en
Publisher: IOS Press
Release Date : 2023-10-03
Knowledge Graphs Semantics Machine Learning And Languages written by M. Acosta and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-03 with Computers categories.
Semantic computing is an integral part of modern technology, an essential component of fields as diverse as artificial intelligence, data science, knowledge discovery and management, big data analytics, e-commerce, enterprise search, technical documentation, document management, business intelligence, and enterprise vocabulary management. This book presents the proceedings of SEMANTICS 2023, the 19th International Conference on Semantic Systems, held in Leipzig, Germany, from 20 to 22 September 2023. The conference is a pivotal event for those professionals and researchers actively engaged in harnessing the power of semantic computing, an opportunity to increase their understanding of the subject’s transformative potential while confronting its practical limitations. Attendees include information managers, IT architects, software engineers, and researchers from a broad spectrum of organizations, including research facilities, non-profit entities, public administrations, and the world's largest corporations. For this year’s conference a total of 54 submissions were received in response to a call for papers. These were subjected to a rigorous, double-blind review process, with at least three independent reviews conducted for each submission. The 16 papers included here were ultimately accepted for presentation, with an acceptance rate of 29.6%. Areas covered include novel research challenges in areas such as data science, machine learning, logic programming, content engineering, social computing, and the Semantic Web. The book provides an up-to-date overview, which will be of interest to all those wishing to stay abreast of emerging trends and themes within the vast field of semantic computing.
Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges
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Author : I. Tiddi
language : en
Publisher: IOS Press
Release Date : 2020-05-06
Knowledge Graphs For Explainable Artificial Intelligence Foundations Applications And Challenges written by I. Tiddi and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-06 with Computers categories.
The latest advances in Artificial Intelligence and (deep) Machine Learning in particular revealed a major drawback of modern intelligent systems, namely the inability to explain their decisions in a way that humans can easily understand. While eXplainable AI rapidly became an active area of research in response to this need for improved understandability and trustworthiness, the field of Knowledge Representation and Reasoning (KRR) has on the other hand a long-standing tradition in managing information in a symbolic, human-understandable form. This book provides the first comprehensive collection of research contributions on the role of knowledge graphs for eXplainable AI (KG4XAI), and the papers included here present academic and industrial research focused on the theory, methods and implementations of AI systems that use structured knowledge to generate reliable explanations. Introductory material on knowledge graphs is included for those readers with only a minimal background in the field, as well as specific chapters devoted to advanced methods, applications and case-studies that use knowledge graphs as a part of knowledge-based, explainable systems (KBX-systems). The final chapters explore current challenges and future research directions in the area of knowledge graphs for eXplainable AI. The book not only provides a scholarly, state-of-the-art overview of research in this subject area, but also fosters the hybrid combination of symbolic and subsymbolic AI methods, and will be of interest to all those working in the field.
Translation Studies In The Age Of Artificial Intelligence
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Author : Sanjun Sun
language : en
Publisher: Taylor & Francis
Release Date : 2025-06-10
Translation Studies In The Age Of Artificial Intelligence written by Sanjun Sun and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-10 with Language Arts & Disciplines categories.
Sun, Liu, Moratto, and the team of contributors provide an in-depth exploration of the implications of artificial intelligence (AI) in the ever-evolving field of translation studies. With key insights to inform future research on this rapidly evolving field in translation, this book offers a comprehensive understanding of the implications of AI, particularly ChatGPT, across technical, pedagogical, and ethical dimensions. From the evolution of translation competence and quality assessment to methodological shifts in research and pedagogy, the authors shed light on the capabilities and limitations of AI, offering insights into its potential within the realm of translation studies. With fresh perspectives on the intersection of AI and translation studies, the chapters cover critical topics such as evaluating translation quality, translator training, corpus translation studies, and ethical considerations in translation education. By systematically unpacking the implications of AI, this book offers valuable insights for researchers, educators, and practitioners interested in translation and interpreting studies, machine-learning, and the role of AI in translator training and education.
Semantic Systems The Power Of Ai And Knowledge Graphs
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Author : Maribel Acosta
language : en
Publisher: Springer Nature
Release Date : 2019-11-04
Semantic Systems The Power Of Ai And Knowledge Graphs written by Maribel Acosta and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-04 with Computers categories.
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.
Applied Graph Data Science
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Author : Pethuru Raj
language : en
Publisher: Elsevier
Release Date : 2025-01-27
Applied Graph Data Science written by Pethuru Raj and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-27 with Computers categories.
Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Use Cases delineates how graph data science significantly empowers the application of data science. The book discusses the emerging paradigm of graph data science in detail along with its practical research and real-world applications. Readers will be enriched with the knowledge of graph data science, graph analytics, algorithms, databases, platforms, and use cases across a variety of research and topics and applications. This book also presents how graphs are used as a programming language, especially demonstrating how Sleptsov Net Computing can contribute as an entirely graphical concurrent processing language for supercomputers. Graph data science is emerging as an expressive and illustrative data structure for optimally representing a variety of data types and their insightful relationships. These data structures include graph query languages, databases, algorithms, and platforms. From here, powerful analytics methods and machine learning/deep learning (ML/DL) algorithms are quickly evolving to analyze and make sense out of graph data. As a result, ground-breaking use cases across scientific research topics and industry verticals are being developed using graph data representation and manipulation. A wide range of complex business and scientific research requirements are efficiently represented and solved through graph data analysis, and Applied Graph Data Science: Graph Algorithms and Platforms, Knowledge Graphs, Neural Networks, and Applied Graph Data Science gives readers both the conceptual foundations and technical methods for applying these powerful techniques. - Provides comprehensive coverage of the emerging paradigm of graph data science and its real-world applications - Gives readers practical guidance on how to approach and solve complex data analysis problems using graph data science, with an emphasis on deep analysis techniques including graph neural networks (GNNs), machine learning, algorithms, graph databases, and graph query languages - Covers extended graph models such as bipartite directed graphs of place-transition nets, graphs with dynamical processes defined on them - Petri and Sleptsov nets, and graphs as programming languages - Presents all the key tools and techniques as well as the foundations of graph theory, including mathematical concepts, research, and graph analytics
Mastering Large Language Models
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Author : Sanket Subhash Khandare
language : en
Publisher: BPB Publications
Release Date : 2024-03-12
Mastering Large Language Models written by Sanket Subhash Khandare and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-12 with Computers categories.
Do not just talk AI, build it: Your guide to LLM application development KEY FEATURES ● Explore NLP basics and LLM fundamentals, including essentials, challenges, and model types. ● Learn data handling and pre-processing techniques for efficient data management. ● Understand neural networks overview, including NN basics, RNNs, CNNs, and transformers. ● Strategies and examples for harnessing LLMs. DESCRIPTION Transform your business landscape with the formidable prowess of large language models (LLMs). The book provides you with practical insights, guiding you through conceiving, designing, and implementing impactful LLM-driven applications. This book explores NLP fundamentals like applications, evolution, components and language models. It teaches data pre-processing, neural networks , and specific architectures like RNNs, CNNs, and transformers. It tackles training challenges, advanced techniques such as GANs, meta-learning, and introduces top LLM models like GPT-3 and BERT. It also covers prompt engineering. Finally, it showcases LLM applications and emphasizes responsible development and deployment. With this book as your compass, you will navigate the ever-evolving landscape of LLM technology, staying ahead of the curve with the latest advancements and industry best practices. WHAT YOU WILL LEARN ● Grasp fundamentals of natural language processing (NLP) applications. ● Explore advanced architectures like transformers and their applications. ● Master techniques for training large language models effectively. ● Implement advanced strategies, such as meta-learning and self-supervised learning. ● Learn practical steps to build custom language model applications. WHO THIS BOOK IS FOR This book is tailored for those aiming to master large language models, including seasoned researchers, data scientists, developers, and practitioners in natural language processing (NLP). TABLE OF CONTENTS 1. Fundamentals of Natural Language Processing 2. Introduction to Language Models 3. Data Collection and Pre-processing for Language Modeling 4. Neural Networks in Language Modeling 5. Neural Network Architectures for Language Modeling 6. Transformer-based Models for Language Modeling 7. Training Large Language Models 8. Advanced Techniques for Language Modeling 9. Top Large Language Models 10. Building First LLM App 11. Applications of LLMs 12. Ethical Considerations 13. Prompt Engineering 14. Future of LLMs and Its Impact
The Semantic Web Iswc 2020
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Author : Jeff Z. Pan
language : en
Publisher: Springer Nature
Release Date : 2020-10-31
The Semantic Web Iswc 2020 written by Jeff Z. Pan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-31 with Computers categories.
The two volume set LNCS 12506 and 12507 constitutes the proceedings of the 19th International Semantic Web Conference, ISWC 2020, which was planned to take place in Athens, Greece, during November 2-6, 2020. The conference changed to a virtual format due to the COVID-19 pandemic. The papers included in this volume deal with the latest advances in fundamental research, innovative technology, and applications of the Semantic Web, linked data, knowledge graphs, and knowledge processing on the Web. They were carefully reviewed and selected for inclusion in the proceedings as follows: Part I: Features 38 papers from the research track which were accepted from 170 submissions; Part II: Includes 22 papers from the resources track which were accepted from 71 submissions; and 21 papers in the in-use track, which had a total of 46 submissions.
Semantic Ai In Knowledge Graphs
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Author : Sanju Tiwari
language : en
Publisher: CRC Press
Release Date : 2023-08-21
Semantic Ai In Knowledge Graphs written by Sanju Tiwari and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-21 with Computers categories.
Recent combinations of semantic technology and artificial intelligence (AI) present new techniques to build intelligent systems that identify more precise results. Semantic AI in Knowledge Graphs locates itself at the forefront of this novel development, uncovering the role of machine learning to extend the knowledge graphs by graph mapping or corpus-based ontology learning. Securing efficient results via the combination of symbolic AI and statistical AI such as entity extraction based on machine learning, text mining methods, semantic knowledge graphs, and related reasoning power, this book is the first of its kind to explore semantic AI and knowledge graphs. A range of topics are covered, from neuro-symbolic AI, explainable AI and deep learning to knowledge discovery and mining, and knowledge representation and reasoning. A trailblazing exploration of semantic AI in knowledge graphs, this book is a significant contribution to both researchers in the field of AI and data mining as well as beginner academicians.