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Table of Contents
Intro; Acknowledgements; Contents; List of Figures; List of Tables; Chapter 1 Introduction; Abstract; References; Chapter 2 M. Ross Quillian, Priming, Spreading-Activation and the Semantic Web; Abstract; 2.1 Computational Groundwork; 2.2 M. Ross Quillian and the Language-Learning Machine; 2.3 Quillian, Collins and Loftus: The Semantic Web and Facilitating Access to the Semantic Memory; 2.4 The Issue of Spreading Activation; 2.5 Quillian and the Psychological Concept of Priming; References; Chapter 3 Where Corpus Linguistics and Artificial Intelligence (AI) Meet; Abstract
3.1 Introduction3.2 From Quillian's Priming to Hoey's Lexical Priming; 3.3 Spreading Activation, Inference and Frame Finding; 3.3.1 Introduction; 3.3.2 The Lack of Understanding in Quillian's Semantic Network and Inference Models to Overcome This Drawback; 3.3.3 More Recent Inference Models Using Frame Semantics; 3.4 From Quillian's Spreading Activation to Edge Pruning; 3.4.1 Introduction; 3.4.2 Spreading Activation Algorithms in the Twenty First Century; 3.4.3 The Small World Network as a Modified Spreading Activation System
3.5 Semantic Spaces, Language Modelling and Deep Neural Networks: Towards Understanding Assistants like Google GO and Apple's SIRI3.5.1 Introduction; 3.5.2 Statistical Prediction Models; 3.5.3 Language Modelling: Long Short-Term Memory (LSTM) and the Recurrent Neural Network (RNN); 3.5.4 Language Models and Speech Recognition; 3.6 A Brief Look at Language Modelling for Translation; References; Chapter 4 Take Home Messages for Linguists and Artificial Intelligence Designers; Abstract; 4.1 Introduction; 4.2 AI Developers-Where They Come from; 4.2.1 Introduction
4.2.2 Philosophers of Language, Linguists and AI Engineers4.3 Learning from Linguists: Language Research Areas; 4.3.1 Introduction; 4.3.2 Learning from Linguists: Language Research Areas; 4.3.3 Learning from Linguists: Hapax Legomena/Rare Words; 4.4 The Structure of Language; References; Chapter 5 Conclusions; Abstract; References; Bibliography: Further Reading; Index
3.1 Introduction3.2 From Quillian's Priming to Hoey's Lexical Priming; 3.3 Spreading Activation, Inference and Frame Finding; 3.3.1 Introduction; 3.3.2 The Lack of Understanding in Quillian's Semantic Network and Inference Models to Overcome This Drawback; 3.3.3 More Recent Inference Models Using Frame Semantics; 3.4 From Quillian's Spreading Activation to Edge Pruning; 3.4.1 Introduction; 3.4.2 Spreading Activation Algorithms in the Twenty First Century; 3.4.3 The Small World Network as a Modified Spreading Activation System
3.5 Semantic Spaces, Language Modelling and Deep Neural Networks: Towards Understanding Assistants like Google GO and Apple's SIRI3.5.1 Introduction; 3.5.2 Statistical Prediction Models; 3.5.3 Language Modelling: Long Short-Term Memory (LSTM) and the Recurrent Neural Network (RNN); 3.5.4 Language Models and Speech Recognition; 3.6 A Brief Look at Language Modelling for Translation; References; Chapter 4 Take Home Messages for Linguists and Artificial Intelligence Designers; Abstract; 4.1 Introduction; 4.2 AI Developers-Where They Come from; 4.2.1 Introduction
4.2.2 Philosophers of Language, Linguists and AI Engineers4.3 Learning from Linguists: Language Research Areas; 4.3.1 Introduction; 4.3.2 Learning from Linguists: Language Research Areas; 4.3.3 Learning from Linguists: Hapax Legomena/Rare Words; 4.4 The Structure of Language; References; Chapter 5 Conclusions; Abstract; References; Bibliography: Further Reading; Index