Practical Guide to Hybrid Natural Language Processing

Combining Neural Models and Knowledge Graphs for NLP

Inbunden, Engelska, 2020

AvJose Manuel Gomez-Perez,Ronald Denaux,Andres Garcia-Silva

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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.

Produktinformation

Utgivningsdatum2020-06-17
Mått155 x 235 x 25 mm
Vikt596 g
FormatInbunden
SpråkEngelska
Antal sidor268
FörlagSpringer Nature Switzerland AG
ISBN9783030448295

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Jose Manuel Gomez-Perez leads the Cogito Research Lab at Expert System in Madrid, Spain, where he focuses on the combination of neural and knowledge-based approaches to enable reading comprehension in machines. His work lies at the intersection of several areas of artificial intelligence, including natural language processing, knowledge graphs and deep learning. He also consults for organizations like the European Space Agency and is the co-founder of ROHub.org, a platform for the intelligent management of scientific information. A former Marie Curie fellow, José Manuel holds a Ph.D. in Computer Science and Artificial Intelligence from Universidad Politécnica de Madrid. He regularly publishes in top scientific conferences and journals and his views have appeared in magazines like Nature and Scientific American, as well as newspapers like El País.Ronald Denaux is a senior researcher scientist at Expert System. Ronald obtained his MSc in Computer Science from the Technical University Eindhoven, The Netherlands. After a couple of years working in industry as a software developer for a large IT company in The Netherlands, Ronald decided to go back to academia. He obtained a Ph.D., again in Computer Science, from the University of Leeds, UK. Ronald’s research interests have revolved around making semantic web technologies more usable for end users, which has required research into the areas of ontology authoring and reasoning, natural language interfaces, dialogue systems, intelligent user interfaces and user modelling. Andres Garcia-Silva is a senior research scientist at Expert System, where he works on a variety of fields related to knowledge management and artificial intelligence including semantic technologies, natural language processing, information extraction and retrieval, and machine learning. Andrés holds a Ph.D. and a Master degree in Artificial Intelligence from Universidad Politécnica de Madrid. He has worked as a visiting researcher at the University of Southampton, the Free University of Berlin, and the University of Southern California. Andrés regularly publishes and reviews papers for conferences and workshops in the semantic web research community.

Part I: Preliminaries and Building Blocks.- Hybrid Natural Language Processing: An Introduction.- Word, Sense, and Graph Embeddings.- UnderstandingWord Embeddings and Language Models.- Capturing Meaning from Text asWord Embeddings.- Capturing Knowledge Graph Embeddings.- Part II: Combining Neural Architectures and Knowledge Graphs.- Building Hybrid Representations from Text Corpora, Knowledge Graphs, and Language Models.- Quality Evaluation.- Capturing Lexical, Grammatical, and Semantic Information with Vecsigrafo.- Aligning Embedding Spaces and Applications for Knowledge Graphs.- Part III: Applications.- A Hybrid Approach to Disinformation Analysis.- Jointly Learning Text and Visual Information in the Scientific Domain.- Looking into the Future of Natural Language Processing.