Table of contents
About this book
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.
- Book Title A Practical Guide to Hybrid Natural Language Processing
- Book Subtitle Combining Neural Models and Knowledge Graphs for NLP
- DOI https://doi.org/10.1007/978-3-030-44830-1
- Copyright Information Springer Nature Switzerland AG 2020
- Publisher Name Springer, Cham
- eBook Packages Computer Science Computer Science (R0)
- Hardcover ISBN 978-3-030-44829-5
- Softcover ISBN 978-3-030-44832-5
- eBook ISBN 978-3-030-44830-1
- Edition Number 1
- Number of Pages XXV, 268
- Number of Illustrations 367 b/w illustrations, 9 illustrations in colour
Information Systems Applications (incl. Internet)
Natural Language Processing (NLP)
- Buy this book on publisher's site
My advice is: Don’t read this book. Use it! Work through its experiments and exercises. Step through the notebooks and see what happens. Then steal the code and build the NLP system you need.
- from the Foreword by Kenneth J. Barker, Manager - Natural Language Analytics, IBM Research, Yorktown Heights, NY, USA