Knowledge Engineering Machine Learning And Lattice Computing With Applications
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| Author | : Manuel Grana |
| Publisher | : Springer |
| Total Pages | : 214 |
| Release | : 2013-03-20 |
| Genre | : Computers |
| ISBN | : 3642373437 |
This book constitutes the refereed proceedings of the 16th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2012, held in San Sebastian, Spain, in September 2012. The 20 revised full papers presented were carefully reviewed and selected from 130 submissions. The papers are organized in topical sections on bioinspired and machine learning methods, machine learning applications, semantics and ontology based techniques, and lattice computing and games.
| Author | : Manuel Graña |
| Publisher | : IOS Press |
| Total Pages | : 2307 |
| Release | : 2012 |
| Genre | : Computers |
| ISBN | : 1614991049 |
In this 2012 edition of Advances in Knowledge-Based and Intelligent Information and Engineering Systems the latest innovations and advances in Intelligent Systems and related areas are presented by leading experts from all over the world. The 228 papers that are included cover a wide range of topics. One emphasis is on Information Processing, which has become a pervasive phenomenon in our civilization. While the majority of Information Processing is becoming intelligent in a very broad sense, major research in Semantics, Artificial Intelligence and Knowledge Engineering supports the domain specific applications that are becoming more and more present in our everyday living. Ontologies play a major role in the development of Knowledge Engineering in various domains, from Semantic Web down to the design of specific Decision Support Systems. Research on Ontologies and their applications is a highly active front of current Computational Intelligence science that is addressed here. Other subjects in this volume are modern Machine Learning, Lattice Computing and Mathematical Morphology.The wide scope and high quality of these contributions clearly show that knowledge engineering is a continuous living and evolving set of technologies aimed at improving the design and understanding of systems and their relations with humans.
| Author | : Vassilis G. Kaburlasos |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 245 |
| Release | : 2007-02-07 |
| Genre | : Computers |
| ISBN | : 3540341706 |
This research monograph proposes a unified, cross-fertilizing approach for knowledge-representation and modeling based on lattice theory. The emphasis is on clustering, classification, and regression applications. It presents novel tools and useful perspectives for effective pattern classification. The material is multi-disciplinary based on on-going research published in major scientific journals and conferences.
| Author | : Alan L. Meyrowitz |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 341 |
| Release | : 2007-08-19 |
| Genre | : Computers |
| ISBN | : 0585273669 |
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.
| Author | : Colette Faucher |
| Publisher | : Springer |
| Total Pages | : 418 |
| Release | : 2013-11-18 |
| Genre | : Technology & Engineering |
| ISBN | : 3319018663 |
This research volume is a continuation of our previous volumes on intelligent machine. It is divided into three parts. Part I deals with big data and ontologies. It includes examples related to the text mining, rule mining and ontology. Part II is on knowledge-based systems. It includes context-centered systems, knowledge discovery, interoperability, consistency and systems of systems. The final part is on applications. The applications involve prediction, decision optimization and assessment. This book is directed to the researchers who wish to explore the field of knowledge engineering further.
| Author | : Siddhartha Bhattacharyya |
| Publisher | : Academic Press |
| Total Pages | : 250 |
| Release | : 2020-03-05 |
| Genre | : Computers |
| ISBN | : 012818700X |
Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. Provides insights into the latest research trends in hybrid intelligent algorithms and architectures Focuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interaction Features hybrid intelligent applications in biomedical engineering and healthcare informatics
| Author | : Lior Rokach |
| Publisher | : Springer Nature |
| Total Pages | : 975 |
| Release | : 2023-08-17 |
| Genre | : Computers |
| ISBN | : 3031246284 |
This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.
| Author | : Alun Preece |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 465 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 1447106512 |
M.A.BRAMER University of Portsmouth, UK This volume comprises the refereed technical papers presented at ES2002, the Twenty-second SGAI International Conference on Knowledge Based Systems and Applied Artificial Intelligence, held in Cambridge in December 2002. The conference was organised by SGAI, the British Computer Society Specialist Group on Artificial Intelligence (previously known as SGES). The papers in this volume present new and innovative developments in the field, divided into sections on Machine Learning, Knowledge Representation and Reasoning, Knowledge Acquisition, Constraint Satisfaction, Scheduling and Natural Language Processing. This year's prize for the best refereed technical paper was won by a paper entitled Covering the Path Space: A Casebase Analysis for Mobile Robot Path Planning by M Kruusmaa (Department of Mechatronics, Tallinn Technical University, Estonia) and J Willemson (Department of Computer Science, Tartu University, Estonia). SGAI gratefully acknowledges the long-term sponsorship of Hewlett-Packard Laboratories (Bristol) for this prize, which goes back to the 1980s. This is the nineteenth volume in the Research and Development series. The Application Stream papers are published as a companion volume under the title Applications and Innovations in Intelligent Systems X. On behalf of the conference organising committee I should like to thank all those who contributed to the organisation of this year's technical programme, in particular the programme committee members, the referees and our administrators Linsay Turbert and Helen Forster.
| Author | : Vassilis G. Kaburlasos |
| Publisher | : Springer |
| Total Pages | : 375 |
| Release | : 2007-06-26 |
| Genre | : Computers |
| ISBN | : 354072687X |
This eighteen-chapter book presents the latest applications of lattice theory in Computational Intelligence (CI). The book focuses on neural computation, mathematical morphology, machine learning, and (fuzzy) inference/logic. The book comes out of a special session held during the World Council for Curriculum and Instruction World Conference (WCCI 2006). The articles presented here demonstrate how lattice theory may suggest viable alternatives in practical clustering, classification, pattern analysis, and regression applications.
| Author | : Damodar Reddy Edla |
| Publisher | : Springer |
| Total Pages | : 383 |
| Release | : 2018-05-16 |
| Genre | : Technology & Engineering |
| ISBN | : 9811085692 |
The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017). The 37 regular papers presented in this volume were carefully reviewed and selected from 123 submissions. These days we find many computer programs that exhibit various useful learning methods and commercial applications. Goal of machine learning is to develop computer programs that can learn from experience. Machine learning involves knowledge from various disciplines like, statistics, information theory, artificial intelligence, computational complexity, cognitive science and biology. For problems like handwriting recognition, algorithms that are based on machine learning out perform all other approaches. Both machine learning and data science are interrelated. Data science is an umbrella term to be used for techniques that clean data and extract useful information from data. In field of data science, machine learning algorithms are used frequently to identify valuable knowledge from commercial databases containing records of different industries, financial transactions, medical records, etc. The main objective of this book is to provide an overview on latest advancements in the field of machine learning and data science, with solutions to problems in field of image, video, data and graph processing, pattern recognition, data structuring, data clustering, pattern mining, association rule based approaches, feature extraction techniques, neural networks, bio inspired learning and various machine learning algorithms.
