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Knowledge Needs and Information Extraction Towards an Artificial Consciousness
ISBN: 9781118574560 | 1118574567
Edition: 1stFormat: eBook
Publisher: Wiley-ISTE
Pub. Date: 1/30/2013
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Amongst the big questions about humanity from “Who am I?” to “Where am I”, there is the subject of consciousness relayed by philosophy and theology at first and then by biology, psychology, sociology and more recently by cognitive sciences. This book attempts to reconcile these disciplines through the common denominator of consciousness, but on one of its specific aspect. The book presents a concept of-motivation of field of activity, as a biological motor of a state of consciousness, and of which system informatics enables to reveal its existence. If consciousness is not well defined, a limited frame provides a more precise and observable definition despite the context complexity of the individuals: psychological, social and technical. These observable elements are of two nature: a nature of principal activity and a cognitive-linguistic nature, which are adapted with extrinsic and intrinsic control factors. The argument presented here consists in presenting a state of consciousness as related to the concept of instinctive (therefore physiological) information need, and whose carrier traces on the traditional information channels, i.e. letters and subscriptions and on the modern information channels, i.e. text messages and web pages, can be analyzed via knowledge extraction.
Chapter 1 – Consciousness, an old and current object of study
Chapter 2 – Self-motivation in daily life
Chapter 3 – The concept of need
Chapter 4 – Models of social organization
Chapter 5 – Theories of the ego
Chapter 6 – Motivational system theories in psychology
Chapter 7 – Motivational system theories in neurosciences
Chapter 8 – Language modeling
Chapter 9 – Computational modeling of motivation
Chapter 10 – Hypothesis and con... MORE
Chapter 11 – A model of self-motivation associating language and physiology
Chapter 12 – Impact of self-motivation on written information
Chapter 13 – Non-transversal techniques of data mining
Chapter 14 – Transversal techniques of data mining
Chapter 15 – Fields of interest of data mining
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