Machine Learning of Natural Language

Machine Learning of Natural Language by David M.W. Powers, Christopher C.R. Turk.

We met because we both share the same views of language. Language is a living organism, produced by neural mechanisms relating in large numbers as a society. Language exists between minds, as a way of communicating between them, not as an autonomous process. The logical 'rules' seem to us...

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Bibliographic Details
Main Authors: Powers, David M.W (Author), Turk, Christopher C.R (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: London : Springer London : Imprint: Springer, 1989.
Edition:1st ed. 1989.
Series:Springer eBook Collection.
Subjects:
Natural language processing (Computer science).
Artificial intelligence.
Electronic resources (E-books)
Online Access:Click to view e-book
Holy Cross Note:Loaded electronically.
Electronic access restricted to members of the Holy Cross Community.
Table of Contents:
  • 1 Art, Science and Engineering
  • Cognitive Structures
  • Scientific Method
  • Language is Contrastive
  • 2 Metaphor as a Cognitive Process
  • Conjecture and Refutation, Theories and Hypotheses
  • Specialization and Abstraction, Induction and Generalization
  • Partial Analysis and Noise
  • The Importance of Errors and Restrictions
  • 3 Psychology and Psycholinguistics
  • The Observable Processes of Acquisition
  • External Influences: Parents, Imitation, and Correction
  • Expansion and Reduction
  • 4 Language Defects and Correction
  • Rate and Order of Learning
  • Telegraphic Speech
  • Parents and Teachers: Good and Bad Examples
  • Reinforcement: Punishment and Reward
  • 5 Cognition and Restriction
  • The Cognitive Processes of Language Acquisition
  • The Magical Number Seven
  • Memory and Capacity Phenomena
  • Adult Characteristics
  • 6 Nativism and Constructivism
  • Representations: Deep Structure and Language Acquisition
  • Acquisition Models, Chomsky and Piaget
  • Computer Programs as Psychological Models
  • 7 Neurology and Neurolinguistics
  • Neuroanatomy: Brains, Neurons, and Synapses
  • Neurophysiology and the Effects of Plasticity
  • Neural Communication and Languages of the Brain
  • Neural Nets: Connectionistic and Locationistic Models
  • 8 The Nature of Language
  • The Quintessence of Language
  • Epistemology, Phonology, and Prosody
  • Culture, Perspectives, and Metaphor
  • 9 The Mechanics of Language
  • Contrast and Similarity: Paradigmatic Learning and Context
  • The Structures of Language
  • Models of Grammar
  • 10 The Ubiquity of the Sentence
  • Pronouns and Anaphora
  • Recursion of Syntax and Parsing
  • Transformational Grammar
  • Generative Grammar
  • Learning Process and Idiolect
  • 11 Computer Science and Artificial Intelligence
  • Pattern Recognition, Problem Solving and Heuristic Search
  • Learning Strategies
  • Problems and Theoretical Limitations
  • 12 Heuristics and Analytic Intransigence
  • Automata and Formal Languages
  • Methodologies: Implementation vs Experimentation
  • Cybernetics and Robotics
  • Deletionless Strategies
  • Formalisms
  • Clauses: Horn and non-Horn, unit and non-unit Systems: LUSH and PROLOG
  • 13 Postulates, Claims and Hypotheses
  • The Bases of Meaning and Learning
  • The Organization of Concepts in Learning
  • The Process of Learning
  • The Artificial Subsumes the Natural
  • 14 Computer Modelling Experiments
  • Batteries One to Seven
  • A Generalized Toy World Package
  • Partial Analysis of NLA
  • Future Systems
  • Conclusions.

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