Download or read book Knowledge Acquisition Approaches Algorithms and Applications written by Debbie Richards and published by Springer. This book was released on 2009-05-13 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly refereed post-workshop proceedings of the 2008 Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, held in Hanoi, Vietnam, in December 2008 as part of 10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008. The 20 revised papers presented were carefully reviewed and selected from 57 submissions and went through two rounds of reviewing and improvement. The papers are organized in topical sections on machine learning and data mining, incremental knowledge acquisition, web-based techniques and applications, as well as domain specific knowledge acquisition methods and applications.
Download or read book New Approaches To Knowledge Acquisition written by Ruqian Lu and published by World Scientific. This book was released on 1994-11-15 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is well recognized that knowledge acquisition is the critical bottleneck of knowledge engineering. This book presents three major approaches of current research in this field, namely the psychological approach, the artificial intelligence approach and the software engineering approach. Special attention is paid to the most recent advances in knowledge acquisition research, especially those made by Chinese computer scientists. A special chapter is devoted to its applications in other fields, e.g. language analysis, software engineering, computer-aided instruction, etc., which were done in China.
Download or read book Knowledge Acquisition and Machine Learning written by Katharina Morik and published by Academic Press. This book was released on 1993-09-13 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: For graduate-/research- level students and professors, this book integrates machine learning with knowledge acquisition to overcome the problems of building models for knowledge-based systems to maintain them successfully. It also reports on BLIP and MOBAL systems developed over the last decade, which illustrate a particular way of unifying knowledge acquisition and machine learning. Practically-orientated, theoretical skills have been used and tested in real-world applications. Integrates machine learning with knowledge acquisition to overcome the problems of building models for knowledge based systems to maintain them successfully Reports on BLIP and MOBAL systems that have been developed over the past 10 years, which illustrate a particular way of unifying knowledge acquisition and machine learning Practically oriented--theoretical results have been used and tested in real-world applications from the start
Download or read book Machine Learning and Knowledge Acquisition written by Gheorghe Tecuci and published by . This book was released on 1995 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Knowledge Acquisition Approaches Algorithms and Applications written by and published by . This book was released on 2007 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Foundations of Knowledge Acquisition written by Alan L. Meyrowitz and published by Springer Science & Business Media. This book was released on 2007-08-19 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Knowledge Acquisition Selected Research and Commentary written by Sandra Marcus and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Knowledge Based Systems written by S. G. Tzafestas and published by World Scientific. This book was released on 1997 with total page 656 pages. Available in PDF, EPUB and Kindle. Book excerpt: The field of knowledge-based systems (KBS) has expanded enormously during the last years, and many important techniques and tools are currently available. Applications of KBS range from medicine to engineering and aerospace.This book provides a selected set of state-of-the-art contributions that present advanced techniques, tools and applications. These contributions have been prepared by a group of eminent researchers and professionals in the field.The theoretical topics covered include: knowledge acquisition, machine learning, genetic algorithms, knowledge management and processing under uncertainty, conflict detection and resolution, structured knowledge architectures, and natural language-based man-machine communication.The Applications include: Real-time decision support, system fault diagnosis, quality assessment, manufacturing production, robotic assembly, and robotic welding.The reader can save considerable time in searching the scattered literature in the field, and can find here a powerful set of how-to-do issues and results.
Download or read book Knowledge Based Systems Four Volume Set written by Cornelius T. Leondes and published by Elsevier. This book was released on 2000-07-11 with total page 1449 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design of knowledge systems is finding myriad applications from corporate databases to general decision support in areas as diverse as engineering, manufacturing and other industrial processes, medicine, business, and economics. In engineering, for example, knowledge bases can be utilized for reliable electric power system operation. In medicine they support complex diagnoses, while in business they inform the process of strategic planning. Programmed securities trading and the defeat of chess champion Kasparov by IBM's Big Blue are two familiar examples of dedicated knowledge bases in combination with an expert system for decision-making. With volumes covering "Implementation," "Optimization," "Computer Techniques," and "Systems and Applications," this comprehensive set constitutes a unique reference source for students, practitioners, and researchers in computer science, engineering, and the broad range of applications areas for knowledge-based systems.
Download or read book Current Trends in Knowledge Acquisition written by Bob Wielinga and published by IOS Press. This book was released on 1990 with total page 390 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Knowledge Acquisition Modeling and Management written by Rudi Studer and published by Springer. This book was released on 2003-06-29 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Past, Present, and Future of Knowledge Acquisition This book contains the proceedings of the 11th European Workshop on Kno- edge Acquisition, Modeling, and Management (EKAW ’99), held at Dagstuhl Castle (Germany) in May of 1999. This continuity and the high number of s- missions re?ect the mature status of the knowledge acquisition community. Knowledge Acquisition started as an attempt to solve the main bottleneck in developing expert systems (now called knowledge-based systems): Acquiring knowledgefromahumanexpert. Variousmethodsandtoolshavebeendeveloped to improve this process. These approaches signi?cantly reduced the cost of - veloping knowledge-based systems. However, these systems often only partially ful?lled the taskthey weredevelopedfor andmaintenanceremainedanunsolved problem. This required a paradigm shift that views the development process of knowledge-based systems as a modeling activity. Instead of simply transf- ring human knowledge into machine-readable code, building a knowledge-based system is now viewed as a modeling activity. A so-called knowledge model is constructed in interaction with users and experts. This model need not nec- sarily re?ect the already available human expertise. Instead it should provide a knowledgelevelcharacterizationof the knowledgethat is requiredby the system to solve the application task. Economy and quality in system development and maintainability are achieved by reusable problem-solving methods and onto- gies. The former describe the reasoning process of the knowledge-based system (i. e. , the algorithms it uses) and the latter describe the knowledge structures it uses (i. e. , the data structures). Both abstract from speci?c application and domain speci?c circumstances to enable knowledge reuse.
Download or read book Ontology Learning and Population from Text written by Philipp Cimiano and published by Springer Science & Business Media. This book was released on 2006-12-11 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade, ontologies have received much attention within computer science and related disciplines, most often as the semantic web. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications discusses ontologies for the semantic web, as well as knowledge management, information retrieval, text clustering and classification, as well as natural language processing. Ontology Learning and Population from Text: Algorithms, Evaluation and Applications is structured for research scientists and practitioners in industry. This book is also suitable for graduate-level students in computer science.
Download or read book Knowledge Engineering Shells written by Nikolaos G. Bourbakis and published by World Scientific. This book was released on 1993 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a systematic approach to knowledge engineering problems. It gives a brief overview of knowledge engineering systems and environments, covering both classical and recent techniques of the design and evaluation of them. Detailed descriptions of particular techniques and applications are also provided.
Download or read book Advanced Methods for Knowledge Discovery from Complex Data written by Ujjwal Maulik and published by Springer Science & Business Media. This book was released on 2006-05-06 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growth in the amount of data collected and generated has exploded in recent times with the widespread automation of various day-to-day activities, advances in high-level scienti?c and engineering research and the development of e?cient data collection tools. This has given rise to the need for automa- callyanalyzingthedatainordertoextractknowledgefromit,therebymaking the data potentially more useful. Knowledge discovery and data mining (KDD) is the process of identifying valid, novel, potentially useful and ultimately understandable patterns from massive data repositories. It is a multi-disciplinary topic, drawing from s- eral ?elds including expert systems, machine learning, intelligent databases, knowledge acquisition, case-based reasoning, pattern recognition and stat- tics. Many data mining systems have typically evolved around well-organized database systems (e.g., relational databases) containing relevant information. But, more and more, one ?nds relevant information hidden in unstructured text and in other complex forms. Mining in the domains of the world-wide web, bioinformatics, geoscienti?c data, and spatial and temporal applications comprise some illustrative examples in this regard. Discovery of knowledge, or potentially useful patterns, from such complex data often requires the - plication of advanced techniques that are better able to exploit the nature and representation of the data. Such advanced methods include, among o- ers, graph-based and tree-based approaches to relational learning, sequence mining, link-based classi?cation, Bayesian networks, hidden Markov models, neural networks, kernel-based methods, evolutionary algorithms, rough sets and fuzzy logic, and hybrid systems. Many of these methods are developed in the following chapters.
Download or read book Rough Set Methods and Applications written by Lech Polkowski and published by Springer Science & Business Media. This book was released on 2000-11-16 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rough set approach to reasoning under uncertainty is based on inducing knowledge representation from data under constraints expressed by discernibility or, more generally, similarity of objects. Knowledge derived by this approach consists of reducts, decision or association rules, dependencies, templates, or classifiers. This monograph presents the state of the art of this area. The reader will find here a deep theoretical discussion of relevant notions and ideas as well as rich inventory of algorithmic and heuristic tools for knowledge discovery by rough set methods. An extensive bibliography will help the reader to get an acquaintance with this rapidly growing area of research.
Download or read book Automated Knowledge Acquisition written by Sabrina Sestito and published by Prentice Hall PTR. This book was released on 1994 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This tutorial provides clear explanations of techniques for automated knowledge acquisition. The techniques covered include: decision tree methods, progressive rule generation, explanation-based learning, artificial neural networks, and genetic algorithm approaches. The book is suitable for both advanced undergraduate and graduate students and computer professionals.
Download or read book Knowledge Management and Acquisition for Smart Systems and Services written by Debbie Richards and published by Springer. This book was released on 2010-08-12 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: th The 11 International Workshop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010) has provided a forum for the past two decades for researchers and practitioners working in the area of machine intelligence. PKAW covers a spectrum of techniques and approaches to implement smartness in IT applications. As evidenced in the papers in this volume, machine intelligence solutions incorporate many areas of AI such as ontological engineering, agent-based techn- ogy, robotics, image recognition and the Semantic Web as well as many other fields of computing such as software engineering, security, databases, the Internet, information retrieval, language technology and game technology. PKAW has evolved to embrace and foster advances in theory, practice and te- nology not only in knowledge acquisition and capture but all aspects of knowledge management including reuse, sharing, maintenance, transfer, merging, reconciliation, creation and dissemination. As many nations strive to be knowledge economies and organizations seek to maximize their knowledge assets and usage, solutions to handle the complex task of knowledge management are more important than ever. This v- ume contributes towards this goal. This volume seeks to disseminate the latest solutions from the International Wo- shop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010) held in Daegu, Korea during August 30–31, 2010 in conjunction with the Pacific Rim International Conference on Artificial Intelligence (PRICAI 2010).
