Machine Learning And Knowledge Acquisition
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Machine Learning And Knowledge Acquisition
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Author : Gheorghe Tecuci
language : en
Publisher:
Release Date : 1995
Machine Learning And Knowledge Acquisition written by Gheorghe Tecuci and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Business & Economics categories.
Currently, both fields are moving towards an integrated approach using machine learning techniques to automate knowledge acquisition from experts, and knowledge acquisition techniques to guide and assist the learning process.
Machine Learning Proceedings 1991
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Author : Lawrence A. Birnbaum
language : en
Publisher: Morgan Kaufmann
Release Date : 2014-06-28
Machine Learning Proceedings 1991 written by Lawrence A. Birnbaum and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-28 with Computers categories.
Machine Learning
Knowledge Acquisition Selected Research And Commentary
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Author : Sandra Marcus
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Knowledge Acquisition Selected Research And Commentary written by Sandra Marcus and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
What follows is a sampler of work in knowledge acquisition. It comprises three technical papers and six guest editorials. The technical papers give an in-depth look at some of the important issues and current approaches in knowledge acquisition. The editorials were pro duced by authors who were basically invited to sound off. I've tried to group and order the contributions somewhat coherently. The following annotations emphasize the connections among the separate pieces. Buchanan's editorial starts on the theme of "Can machine learning offer anything to expert systems?" He emphasizes the practical goals of knowledge acquisition and the challenge of aiming for them. Lenat's editorial briefly describes experience in the development of CYC that straddles both fields. He outlines a two-phase development that relies on an engineering approach early on and aims for a crossover to more automated techniques as the size of the knowledge base increases. Bareiss, Porter, and Murray give the first technical paper. It comes from a laboratory of machine learning researchers who have taken an interest in supporting the development of knowledge bases, with an emphasis on how development changes with the growth of the knowledge base. The paper describes two systems. The first, Protos, adjusts the training it expects and the assistance it provides as its knowledge grows. The second, KI, is a system that helps integrate knowledge into an already very large knowledge base.
Machine Learning
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Author : Tom M. Mitchell
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Machine Learning written by Tom M. Mitchell and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed.
Foundations Of Knowledge Acquisition
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Author : Alan L. Meyrowitz
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-08-19
Foundations Of Knowledge Acquisition written by Alan L. Meyrowitz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-19 with Computers categories.
One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact of successful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain about the methods by which machines and humans might learn, significant progress has been made.
Foundations Of Knowledge Acquisition
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Author : Susan Chipman
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Foundations Of Knowledge Acquisition written by Susan Chipman and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
One of the most intriguing questions about the new computer technology that has appeared over the past few decades is whether we humans will ever be able to make computers learn. As is painfully obvious to even the most casual computer user, most current computers do not. Yet if we could devise learning techniques that enable computers to routinely improve their performance through experience, the impact would be enormous. The result would be an explosion of new computer applications that would suddenly become economically feasible (e. g. , personalized computer assistants that automatically tune themselves to the needs of individual users), and a dramatic improvement in the quality of current computer applications (e. g. , imagine an airline scheduling program that improves its scheduling method based on analyzing past delays). And while the potential economic impact ofsuccessful learning methods is sufficient reason to invest in research into machine learning, there is a second significant reason: studying machine learning helps us understand our own human learning abilities and disabilities, leading to the possibility of improved methods in education. While many open questions remain aboutthe methods by which machines and humans might learn, significant progress has been made.
Current Trends In Knowledge Acquisition
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Author : Bob Wielinga
language : en
Publisher: IOS Press
Release Date : 1990
Current Trends In Knowledge Acquisition written by Bob Wielinga and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with Computers categories.
Knowledge acquisition has become a major area of artificial intelligence and cognitive science research. The papers in this book show that the area of knowledge acquisition for knowledge-based systems is still a diverse field in which a large number of research topics are being addressed. However, several main themes run through the papers. First, the issues of integrating knowledge from different sources and K.A. tools is a salient topic in many papers. A second major topic in the papers is that of knowledge modelling. Research in knowledge-based systems emphasises the use of generic models of reasoning and its underlying knowledge. An important trend in the area of knowledge modelling aims at the formalisation of knowledge models. Where the field of knowledge acquisition was without tools and techniques years ago, now there is a rapidly growing body of techniques and tools. Apart from the integrated workbenches already mentioned above, several papers in this book present new tools. Although knowledge acquisition and machine learning have been considered as separate subfields of AI, there is a tendency for the two fields to come together. This publication combines machine learning techniques with more conventional knowledge elicitation techniques. A framework is presented in which reasoning, problem solving and learning together form a knowledge intensive system that can acquire knowledge from its own experience.
Machine Learning Methods For Commonsense Reasoning Processes Interactive Models
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Author : Naidenova, Xenia
language : en
Publisher: IGI Global
Release Date : 2009-10-31
Machine Learning Methods For Commonsense Reasoning Processes Interactive Models written by Naidenova, Xenia and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-31 with Computers categories.
This book suggests that classification is a key to human commonsense reasoning and transforms traditional considerations of data and knowledge communications, presenting an effective classification of logical rules used in the modeling of commonsense reasoning.