This book presents a theory of consciousness which is unique and sustainable in nature, based on physiological and cognitive-linguistic principles controlled by a number of socio-psycho-economic factors. In order to anchor this theory, which draws upon various disciplines, the author presents a number of different theories, all of which have been abundantly studied by scientists from both a theoretical and experimental standpoint, including models of social organization, ego theories, theories of the motivational system in psychology, theories of the motivational system in neurosciences, language modeling and computational modeling of motivation.
The theory presented in this book is based on the hypothesis that an individual's main activities are developed by self-motivation, managed as an informational need. This is described in chapters covering self-motivation on a day-to-day basis, the notion of need, the hypothesis and control of cognitive self-motivation and a model of self-motivation which associates language and physiology. The subject of knowledge extraction is also covered, including the impact of self-motivation on written information, non-transversal and transversal text-mining techniques and the fields of interest of text mining.
1. Consciousness: an Ancient and Current Topic of Study.
2. Self-motivation on a Daily Basis.
3. The Notion of Need.
4. The Models of Social Organization.
5. Self Theories.
6. Theories of Motivation in Psychology.
7. Theories of Motivation in Neurosciences.
8. Language Modeling.
9. Computational Modeling of Motivation.
10. Hypothesis and Control of Cognitive Self-Motivation.
11. A Model of Self-Motivation which Associates Language and Physiology.
12. Impact of Self-Motivation on Written Information.
13. Non-Transversal Text Mining Techniques.
14. Transversal Text Mining Techniques.
15. Fields of Interest for Text Mining.
About the Authors
Nicolas Turenne is a researcher at INRA in the Science and Society team at the University of Paris-Est Marne la Vallée in France. He specializes in knowledge extraction from texts with theoretical research into relational and stochastic models. His research topics also concern the sociology of uses, food and environmental sciences, and bioinformatics.
Table of Contents
- Title page
- Copyright page
- Chapter 1: Consciousness: an Ancient and Current Topic of Study
- Chapter 2: Self-motivation on a Daily Basis
- Chapter 3: The Notion of Need
- Chapter 4: The Models of Social Organization
- Chapter 5: Self Theories
Chapter 6: Theories of Motivation in Psychology
- 6.1. Behavior and cognition
- 6.2. Theory of self-efficacy
- 6.3. Theory of self-determination
- 6.4. Theory of control
- 6.5. Attribution theory
- 6.6. Standards and self-regulation
- 6.7. Deviance and pathology
- 6.8. Temporal Motivation Theory
- 6.9. Effect of objectives
- 6.10. Context of distance learning
- 6.11. Maintenance model
- 6.12. Effect of narrative
- 6.13. Effect of eviction
- 6.14. Effect of the teacher–student relationship
- 6.15. Model of persistence and change
- 6.16. Effect of the man–machine relationship
- Chapter 7: Theories of Motivation in Neurosciences
Chapter 8: Language Modeling
- 8.1. Issues surrounding language
- 8.2. Interaction and language
- 8.3. Development and language
- 8.4. Schools of thought in linguistic sciences
- 8.5. Semantics and combination
- 8.6. Functional grammar
- 8.7. Meaning-Text Theory
- 8.8. Generative lexicon
- 8.9. Theory of synergetic linguistics
- 8.10. Integrative approach to language processing
- 8.11. New spaces for date production
- 8.12. Notion of ontology
- 8.13. Knowledge representation
- Chapter 9: Computational Modeling of Motivation
- Chapter 10: Hypothesis and Control of Cognitive Self-Motivation
Chapter 11: A Model of Self-Motivation which Associates Language and Physiology
- 11.1. A new model
- 11.2. Architecture of a self-motivation subsystem
- 11.3. Level of certainty
- 11.4. Need for self-motivation
- 11.5. Notion of motive
- 11.6. Age and location
- 11.7. Uniqueness
- 11.8. Effect of spontaneity
- 11.9. Effect of dependence
- 11.10. Effect of emulation
- 11.11. Transition of belief
- 11.12. Effect of individualism
- 11.13. Modeling of the groups of beliefs
Chapter 12: Impact of Self-Motivation on Written Information
- 12.1. Platform for production and consultation of texts
- 12.2. Informational measure of the motives of self-motivation
- 12.3. The information market
- 12.4. Types of data
- 12.5. The outlines of text mining
- 12.6. Software economy
- 12.7. Standards and metadata
- 12.8. Open-ended questions and challenges for text-mining methods
- 12.9. Notion of lexical noise
- 12.10. Web mining
- 12.11. Mining approach
Chapter 13: Non-Transversal Text Mining Techniques
- 13.1. Constructivist activity
- 13.2. Typicality associated with the data
- 13.3. Specific character of text mining
- 13.4.Supervised, unsupervised and semi-supervised techniques
- 13.5.Quality of a model
- 13.6. The scenario
- 13.7. Representation of a datum
- 13.8. Standardization
- 13.9. Morphological preprocessing
- 13.10. Selection and weighting of terminological units
- 13.11. Statistical properties of textual units: lexical laws
- 13.12. Sub-lexical units
- 13.14. Shallow parsing or superficial syntactic analysis
- 13.15. Argumentation models
Chapter 14: Transversal Text Mining Techniques
- 14.1. Mixed and interdisciplinary text mining techniques
- 14.2. Techniques for extraction of named entities
- 14.3. Inverse methods
- 14.4. Latent Semantic Analysis
- 14.5. Iterative construction of sub-corpora
- 14.6. Ordering approaches or ranking method
- 14.7. Use of ontology
- 14.8. Interdisciplinary techniques
- 14.9. Information visualization techniques
- 14.10. The k-means technique
- 14.11. Naive Bayes classifier technique
- 14.12. The k-nearest neighbors (KNN) technique
- 14.13. Hierarchical clustering technique
- 14.14. Density-based clustering techniques
- 14.15. Conditional fields
- 14.16. Nonlinear regression and artificial neural networks
- 14.17. Models of multi-agent systems (MASs)
- 14.18. Co-clustering models
- 14.19. Dependency models
- 14.20. Decision tree technique
- 14.21. The Support Vector Machine (SVM) technique
- 14.22. Set of frequent items
- 14.23. Genetic algorithms
- 14.24. Link analysis with a theoretical graph model
- 14.25. Link analysis without a graph model
- 14.26. Quality of a model
- 14.27. Model selection
- Chapter 15: Fields of Interest for Text Mining
- Title: Knowledge Needs and Information Extraction: Towards an Artificial Consciousness
- Release date: March 2013
- Publisher(s): Wiley
- ISBN: 9781118574591