• Title Natural Language Processing Techniques in Prolog
• Author(s) Patrick Blackburn, Kristina Striegnitz
• Publisher: O'Reilly Media; 1 edition (July 7, 2009); eBook (Union College, Lecture Notes)
• Paperback: N/A
• eBook: HTML
• Language: English
• ISBN-10: N/A
• ISBN-13: N/A
• Share This:  

Book Description

Research into Natural Language Processing - the use of computers to process language - has developed over the last couple of decades into one of the most vigorous and interesting areas of current work on language and communication.

This book introduces the subject through the discussion and development of various computer programs which illustrate some of the basic concepts and techniques in the field. The programming language used is Prolog, which is especially well-suited for Natural Language Processing and those with little or no background in computing. Following the general introduction, the first section of the book presents Prolog, and the following chapters illustrate how various Natural Language Processing programs may be written using this programming language.

Since it is assumed that the reader has no previous experience in programming, great care is taken to provide a simple yet comprehensive introduction to Prolog. Due to the 'user friendly' nature of Prolog, simple yet effective programs may be written from an early stage. The reader is gradually introduced to various techniques for syntactic processing, ranging from Finite State Network recognisors to Chart parsers. An integral element of the book is the comprehensive set of exercises included in each chapter as a means of cementing the reader's understanding of each topic. Suggested answers are also provided. An Introduction to Natural Language Processing Through Prolog is an excellent introduction to the subject for students of linguistics and computer science, and will be especially useful for those with no background in the subject.

Contents: Finite State Automata; Finite State Parsers and Transducers; Finite State Methods in Natural Language Processing; Recursive Transition Networks (RTNs); RTN transducers and ATNs; Definite Clause Grammars; Bottom Up Parsing; Top Down Parsing; Using Bottom Up and Top Down Information for Parsing; Passive Chart Parsing; Bottom-up Active Chart Parsing; Top-down Active Chart Parsing; Feature Structures; Parsing Feature-based Grammars; Natural Language Generation - A Top-down Generator.

• N/A

• Amazon

• Natural Language Processing (NLP)
• Prolog Programming
• Deep Learning and Neural Networks

• Natural Language Processing Techniques in Prolog (Patrick Blackburn, et al)

• Natural Language Processing for Prolog Programmers

  An examination of natural language processing in Prolog for those who know Prolog but not linguistics, this book enables students to move quickly into writing and working in useful software for natural language processing (NLP).

• Prolog and Natural-Language Analysis (Fernando Pereira, et al)

  A concise and practical introduction to logic programming and the language Prolog both as vehicles for understanding elementary computational linguistics and as tools for implementing the basic components of natural-language-processing (NLP) systems.

• Foundations of Large Language Models (Tong Xiao, et al.)

  This is a book about Large Language Models (LLM). It primarily focuses on foundational concepts rather than comprehensive coverage of all cutting-edge technologies: pre-training, generative models, prompting techniques, and alignment methods.

• Large Language Models in Cybersecurity: Threats and Mitigation

  This open access book provides cybersecurity practitioners with the knowledge needed to understand the risks of the increased availability of powerful Large Language Models (LLM) and how they can be mitigated.

• Understanding Large Language Models (Jenny Kunz)

  This practical book offers clear, example-rich explanations of how Large Language Models (LLM) work, how you can interact with them, and how to integrate LLMs into your own applications.

• Foundation Models for Natural Language Processing

  This open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts.

• Speech and Language Processing (Dan Jurafsky, et al)

  This text takes an empirical approach to the subject, based on applying statistical and other machine-learning algorithms to large corporations. It describes a unified vision of speech and language processing. Emphasis is on practical and scientific applications.