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Author: Heiko Paulheim
Publisher: Springer Nature
ISBN: 3031303873
Category : Computers
Languages : en
Pages : 165
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Book Description
This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained knowledge graph embeddings to training tailored vectors for a knowledge graph at hand. They also demonstrate different extensions of RDF2vec and how they affect not only the downstream performance, but also the expressivity of the resulting vector representation, and analyze the resulting vector spaces and the semantic properties they encode.
Author: Heiko Paulheim
Publisher: Springer Nature
ISBN: 3031303873
Category : Computers
Languages : en
Pages : 165
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Book Description
This book explains the ideas behind one of the most well-known methods for knowledge graph embedding of transformations to compute vector representations from a graph, known as RDF2vec. The authors describe its usage in practice, from reusing pre-trained knowledge graph embeddings to training tailored vectors for a knowledge graph at hand. They also demonstrate different extensions of RDF2vec and how they affect not only the downstream performance, but also the expressivity of the resulting vector representation, and analyze the resulting vector spaces and the semantic properties they encode.
Author: Ulrike Sattler
Publisher: Springer Nature
ISBN: 3031194330
Category : Computers
Languages : en
Pages : 899
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Book Description
This book constitutes the proceedings of the 21st International Semantic Web Conference, ISWC 2022, which took place in October 2022 in a virtual mode. The 48 full papers presented in this volume were thoroughly reviewed and selected from 239 submissions. They 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. Papers are organized in a research track, resources and in-use track. The research track details theoretical, analytical and empirical aspects of the Semantic Web and its intersection with other disciplines. The resources track promotes the sharing of resources which support, enable or utilize semantic web research, including datasets, ontologies, software, and benchmarks. And finally, the in-use-track is dedicated to novel and significant research contributions addressing theoretical, analytical and empirical aspects of the Semantic Web and its intersection with other disciplines. The chapters "Hashing the Hypertrie: Space- and Time-Efficient Indexing for SPARQL in Tensors", "Agree to Disagree: Managing Ontological Perspectives using Standpoint Logic", "GNNQ: A Neuro-Symbolic Approach to Query Answering over Incomplete Knowledge Graphs", "ISSA: Generic Pipeline, Knowledge Model and Visualization tools to Help Scientists Search and Make Sense of a Scientific Archiveare" are licensed under the terms of the Creative Commons Attribution 4.0 International License.
Author: Andreas Hotho
Publisher: Springer Nature
ISBN: 3030883612
Category : Computers
Languages : en
Pages : 756
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Book Description
This book constitutes the proceedings of the 20th International Semantic Web Conference, ISWC 2021, which took place in October 2021. Due to COVID-19 pandemic the conference was held virtually. 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. Papers are organized in a research track, resources and in-use track. The research track details theoretical, analytical and empirical aspects of the Semantic Web and its intersection with other disciplines. The resources track promotes the sharing of resources which support, enable or utilize semantic web research, including datasets, ontologies, software, and benchmarks. And finally, the in-use-track is dedicated to novel and significant research contributions addressing theoretical, analytical and empirical aspects of the Semantic Web and its intersection with other disciplines.
Author: Paul Groth
Publisher: Springer Nature
ISBN: 3031116097
Category : Computers
Languages : en
Pages : 332
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Book Description
This book constitutes the proceedings of the satellite events held at the 19th Extended Semantic Web Conference, ESWC 2022, during May—June in Hersonissos, Greece, 2022. The included satellite events are: the poster and demo session; the PhD symposium; industry track; project networking; workshops and tutorials. During ESWC 2022, the following ten workshops took place:10th Linked Data in Architecture and Construction Workshop (LDAC 2022); 5th International Workshop on Geospatial Linked Data (GeoLD 2022); 5th Workshop on Semantic Web solutions for large-scale biomedical data analytics (SeMWeBMeDA 2022); 7th Natural Language Interfaces for the Web of Data (NLIWOD+QALD 2022); International Workshop on Knowledge Graph Generation from Text (Text2KG 2022); 3rd International Workshop on Deep Learning meets Ontologies and Natural Language Processing (DeepOntoNLP 2022); 1st Workshop on Modular Knowledge (ModularK 2022); Third International Workshop On Knowledge Graph Construction (KGCW 2022); Third International Workshop On Semantic Digital Twins (SeDIT 2022); and the 1st International Workshop on Semantic Industrial Information Modelling (SemIIM 2022).
Author: Aidan Hogan
Publisher: Morgan & Claypool Publishers
ISBN: 1636392369
Category : Computers
Languages : en
Pages : 257
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Book Description
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: Jose Manuel Gomez-Perez
Publisher: Springer Nature
ISBN: 3030448304
Category : Computers
Languages : en
Pages : 281
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Book Description
This book provides readers with a practical guide to the principles of hybrid approaches to natural language processing (NLP) involving a combination of neural methods and knowledge graphs. To this end, it first introduces the main building blocks and then describes how they can be integrated to support the effective implementation of real-world NLP applications. To illustrate the ideas described, the book also includes a comprehensive set of experiments and exercises involving different algorithms over a selection of domains and corpora in various NLP tasks. Throughout, the authors show how to leverage complementary representations stemming from the analysis of unstructured text corpora as well as the entities and relations described explicitly in a knowledge graph, how to integrate such representations, and how to use the resulting features to effectively solve NLP tasks in a range of domains. In addition, the book offers access to executable code with examples, exercises and real-world applications in key domains, like disinformation analysis and machine reading comprehension of scientific literature. All the examples and exercises proposed in the book are available as executable Jupyter notebooks in a GitHub repository. They are all ready to be run on Google Colaboratory or, if preferred, in a local environment. A valuable resource for anyone interested in the interplay between neural and knowledge-based approaches to NLP, this book is a useful guide for readers with a background in structured knowledge representations as well as those whose main approach to AI is fundamentally based on logic. Further, it will appeal to those whose main background is in the areas of machine and deep learning who are looking for ways to leverage structured knowledge bases to optimize results along the NLP downstream.
Author: Chiara Ghidini
Publisher: Springer Nature
ISBN: 303030793X
Category : Computers
Languages : en
Pages : 794
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Book Description
The two-volume set of LNCS 11778 and 11779 constitutes the refereed proceedings of the 18th International Semantic Web Conference, ISWC 2019, held in Auckland, New Zealand, in October 2019. The ISWC conference is the premier international forum for the Semantic Web / Linked Data Community. The total of 74 full papers included in this volume was selected from 283 submissions. The conference is organized in three tracks: for the Research Track 42 full papers were selected from 194 submissions; the Resource Track contains 21 full papers, selected from 64 submissions; and the In-Use Track features 11 full papers which were selected from 25 submissions to this track.
Author: Leonard Barolli
Publisher: Springer
ISBN: 3319935542
Category : Technology & Engineering
Languages : en
Pages : 987
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Book Description
This book presents the latest research findings, methods and development techniques related to Ubiquitous and Pervasive Computing (UPC) as well as challenges and solutions from both theoretical and practical perspectives with an emphasis on innovative, mobile and internet services. With the proliferation of wireless technologies and electronic devices, there is a rapidly growing interest in Ubiquitous and Pervasive Computing (UPC). UPC makes it possible to create a human-oriented computing environment where computer chips are embedded in everyday objects and interact with physical world. It also allows users to be online even while moving around, providing them with almost permanent access to their preferred services. Along with a great potential to revolutionize our lives, UPC also poses new research challenges.
Author: Uday Kamath
Publisher: Springer
ISBN: 3030145964
Category : Computers
Languages : en
Pages : 640
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Book Description
This textbook explains Deep Learning Architecture, with applications to various NLP Tasks, including Document Classification, Machine Translation, Language Modeling, and Speech Recognition. With the widespread adoption of deep learning, natural language processing (NLP),and speech applications in many areas (including Finance, Healthcare, and Government) there is a growing need for one comprehensive resource that maps deep learning techniques to NLP and speech and provides insights into using the tools and libraries for real-world applications. Deep Learning for NLP and Speech Recognition explains recent deep learning methods applicable to NLP and speech, provides state-of-the-art approaches, and offers real-world case studies with code to provide hands-on experience. Many books focus on deep learning theory or deep learning for NLP-specific tasks while others are cookbooks for tools and libraries, but the constant flux of new algorithms, tools, frameworks, and libraries in a rapidly evolving landscape means that there are few available texts that offer the material in this book. The book is organized into three parts, aligning to different groups of readers and their expertise. The three parts are: Machine Learning, NLP, and Speech Introduction The first part has three chapters that introduce readers to the fields of NLP, speech recognition, deep learning and machine learning with basic theory and hands-on case studies using Python-based tools and libraries. Deep Learning Basics The five chapters in the second part introduce deep learning and various topics that are crucial for speech and text processing, including word embeddings, convolutional neural networks, recurrent neural networks and speech recognition basics. Theory, practical tips, state-of-the-art methods, experimentations and analysis in using the methods discussed in theory on real-world tasks. Advanced Deep Learning Techniques for Text and Speech The third part has five chapters that discuss the latest and cutting-edge research in the areas of deep learning that intersect with NLP and speech. Topics including attention mechanisms, memory augmented networks, transfer learning, multi-task learning, domain adaptation, reinforcement learning, and end-to-end deep learning for speech recognition are covered using case studies.
Author: P. Hitzler
Publisher: IOS Press
ISBN: 1643682458
Category : Computers
Languages : en
Pages : 410
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Book Description
Neuro-symbolic AI is an emerging subfield of Artificial Intelligence that brings together two hitherto distinct approaches. ”Neuro” refers to the artificial neural networks prominent in machine learning, ”symbolic” refers to algorithmic processing on the level of meaningful symbols, prominent in knowledge representation. In the past, these two fields of AI have been largely separate, with very little crossover, but the so-called “third wave” of AI is now bringing them together. This book, Neuro-Symbolic Artificial Intelligence: The State of the Art, provides an overview of this development in AI. The two approaches differ significantly in terms of their strengths and weaknesses and, from a cognitive-science perspective, there is a question as to how a neural system can perform symbol manipulation, and how the representational differences between these two approaches can be bridged. The book presents 17 overview papers, all by authors who have made significant contributions in the past few years and starting with a historic overview first seen in 2016. With just seven months elapsed from invitation to authors to final copy, the book is as up-to-date as a published overview of this subject can be. Based on the editors’ own desire to understand the current state of the art, this book reflects the breadth and depth of the latest developments in neuro-symbolic AI, and will be of interest to students, researchers, and all those working in the field of Artificial Intelligence.
