Uncertainty and Vagueness in Knowledge Based Systems

Uncertainty and Vagueness in Knowledge Based Systems
Author :
Publisher : Springer Science & Business Media
Total Pages : 495
Release :
ISBN-10 : 9783642767029
ISBN-13 : 3642767028
Rating : 4/5 (29 Downloads)

Book Synopsis Uncertainty and Vagueness in Knowledge Based Systems by : Rudolf Kruse

Download or read book Uncertainty and Vagueness in Knowledge Based Systems written by Rudolf Kruse and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 495 pages. Available in PDF, EPUB and Kindle. Book excerpt: The primary aim of this monograph is to provide a formal framework for the representation and management of uncertainty and vagueness in the field of artificial intelligence. It puts particular emphasis on a thorough analysis of these phenomena and on the development of sound mathematical modeling approaches. Beyond this theoretical basis the scope of the book includes also implementational aspects and a valuation of existing models and systems. The fundamental ambition of this book is to show that vagueness and un certainty can be handled adequately by using measure-theoretic methods. The presentation of applicable knowledge representation formalisms and reasoning algorithms substantiates the claim that efficiency requirements do not necessar ily require renunciation of an uncompromising mathematical modeling. These results are used to evaluate systems based on probabilistic methods as well as on non-standard concepts such as certainty factors, fuzzy sets or belief functions. The book is intended to be self-contained and addresses researchers and practioneers in the field of knowledge based systems. It is in particular suit able as a textbook for graduate-level students in AI, operations research and applied probability. A solid mathematical background is necessary for reading this book. Essential parts of the material have been the subject of courses given by the first author for students of computer science and mathematics held since 1984 at the University in Braunschweig.

Introduction to Knowledge Systems

Introduction to Knowledge Systems
Author :
Publisher : Morgan Kaufmann
Total Pages : 906
Release :
ISBN-10 : UOM:39015037326207
ISBN-13 :
Rating : 4/5 (07 Downloads)

Book Synopsis Introduction to Knowledge Systems by : Mark Stefik

Download or read book Introduction to Knowledge Systems written by Mark Stefik and published by Morgan Kaufmann. This book was released on 1995 with total page 906 pages. Available in PDF, EPUB and Kindle. Book excerpt: The art of building knowledge systems is multidisciplinary, incorporating computer science theory, programming practice and psychology. This book incorporates these varied fields covering topics ranging from algorithms and representations to techniques for acquiring the task specific knowledge.

Uncertainty in Knowledge Bases

Uncertainty in Knowledge Bases
Author :
Publisher : Springer Science & Business Media
Total Pages : 630
Release :
ISBN-10 : 3540543465
ISBN-13 : 9783540543466
Rating : 4/5 (65 Downloads)

Book Synopsis Uncertainty in Knowledge Bases by : Bernadette Bouchon-Meunier

Download or read book Uncertainty in Knowledge Bases written by Bernadette Bouchon-Meunier and published by Springer Science & Business Media. This book was released on 1991-09-11 with total page 630 pages. Available in PDF, EPUB and Kindle. Book excerpt: One out of every two men over eigthy suffers from carcinoma of the prostate.It is discovered incidentally in many patients with an alleged benign prostatic hyperplasia. In treating patients, the authors make clear that primary radical prostatectomy is preferred over transurethral resection due to the lower complication rate.

Symbolic and Quantitative Approaches to Uncertainty

Symbolic and Quantitative Approaches to Uncertainty
Author :
Publisher : Springer Science & Business Media
Total Pages : 380
Release :
ISBN-10 : 3540546596
ISBN-13 : 9783540546597
Rating : 4/5 (96 Downloads)

Book Synopsis Symbolic and Quantitative Approaches to Uncertainty by : Rudolf Kruse

Download or read book Symbolic and Quantitative Approaches to Uncertainty written by Rudolf Kruse and published by Springer Science & Business Media. This book was released on 1991-10 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: A variety of formalisms have been developed to address such aspects of handling imperfect knowledge as uncertainty, vagueness, imprecision, incompleteness, and partial inconsistency. Some of the most familiar approaches in this research field are nonmonotonic logics, modal logics, probability theory (Bayesian and non-Bayesian), belief function theory, and fuzzy sets and possibility theory. ESPRIT Basic Research Action 3085, entitled Defeasible Reasoning and Uncertainty Management Systems (DRUMS), aims to contribute to the elucidation of similarities and differences between these formalisms. It consists of 11 active European research groups. The European Conference on Symbolic and Quantitative Approaches to Uncertainty (ESQAU) provides a forum for these groups to meet and discuss their scientific results. This volume contains 42 contributions accepted for the ESQAU meeting held in October 1991 in Marseille, together with 12 articles presenting the activities of the DRUMS groups and two invited presentations.

Expert System Applications

Expert System Applications
Author :
Publisher : Springer Science & Business Media
Total Pages : 475
Release :
ISBN-10 : 9783642833144
ISBN-13 : 3642833144
Rating : 4/5 (44 Downloads)

Book Synopsis Expert System Applications by : Leonard Bolc

Download or read book Expert System Applications written by Leonard Bolc and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: While expert systems technology originated in the United States, its development has become an international concern. Since the start of the DENDRAL project at Stanford University over 15 years ago, with its objective of problem-solving via the automation of actual human expert knowledge, significant expert systems projects have been completed in countries rang ing from Japan to France, Spain to China. This book presents a sample of five such projects, along with four substantial reports of mature studies from North American researchers. Two important issues of expert system design permeate the papers in this volume. The first concerns the incorporation of substantial numeric knowledge into a system. This has become a significant focus of work as researchers have sought to apply expert systems tech nology to complex, real-world domains already subject to statistical or algebraic description (and handled well at some level in numeric terms). A second prominent issue is that of representing control knowledge in a manner which is both explicit, and thus available for inspection, and compatible with the semantics of the problem domain.

Flexible Approaches in Data, Information and Knowledge Management

Flexible Approaches in Data, Information and Knowledge Management
Author :
Publisher : Springer
Total Pages : 320
Release :
ISBN-10 : 9783319009544
ISBN-13 : 3319009540
Rating : 4/5 (44 Downloads)

Book Synopsis Flexible Approaches in Data, Information and Knowledge Management by : Olivier Pivert

Download or read book Flexible Approaches in Data, Information and Knowledge Management written by Olivier Pivert and published by Springer. This book was released on 2013-09-12 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume showcases contributions from internationally-known researchers in the field of information management. Most of the approaches presented here make use of fuzzy logic, introduced by L.A. Zadeh almost 50 years ago, which constitute a powerful tool to model and handle gradual concepts. What all of these contributions have in common is placing the user at the center of the information system, be it for helping him/her to query a data set, to handle imperfect information, or to discover useful knowledge from a massive collection of data. Researchers working in data and knowledge management will greatly benefit from this collection of up-to-date studies. This may be also an invaluable source of information for postgraduate students interested in advanced information management techniques.

Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering

Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering
Author :
Publisher : Springer
Total Pages : 271
Release :
ISBN-10 : 9783319494937
ISBN-13 : 3319494937
Rating : 4/5 (37 Downloads)

Book Synopsis Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering by : Jeff Z. Pan

Download or read book Reasoning Web: Logical Foundation of Knowledge Graph Construction and Query Answering written by Jeff Z. Pan and published by Springer. This book was released on 2017-02-28 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains some lecture notes of the 12th Reasoning Web Summer School (RW 2016), held in Aberdeen, UK, in September 2016. In 2016, the theme of the school was “Logical Foundation of Knowledge Graph Construction and Query Answering”. The notion of knowledge graph has become popular since Google started to use it to improve its search engine in 2012. Inspired by the success of Google, knowledge graphs are gaining momentum in the World Wide Web arena. Recent years have witnessed increasing industrial take-ups by other Internet giants, including Facebook's Open Graph and Microsoft's Satori. The aim of the lecture note is to provide a logical foundation for constructing and querying knowledge graphs. Our journey starts from the introduction of Knowledge Graph as well as its history, and the construction of knowledge graphs by considering both explicit and implicit author intentions. The book will then cover various topics, including how to revise and reuse ontologies (schema of knowledge graphs) in a safe way, how to combine navigational queries with basic pattern matching queries for knowledge graph, how to setup a environment to do experiments on knowledge graphs, how to deal with inconsistencies and fuzziness in ontologies and knowledge graphs, and how to combine machine learning and machine reasoning for knowledge graphs.