Uncertainty Management in Information Systems

Uncertainty Management in Information Systems

Author: Amihai Motro

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 473

ISBN-13: 1461562457

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As its title suggests, "Uncertainty Management in Information Systems" is a book about how information systems can be made to manage information permeated with uncertainty. This subject is at the intersection of two areas of knowledge: information systems is an area that concentrates on the design of practical systems that can store and retrieve information; uncertainty modeling is an area in artificial intelligence concerned with accurate representation of uncertain information and with inference and decision-making under conditions infused with uncertainty. New applications of information systems require stronger capabilities in the area of uncertainty management. Our hope is that lasting interaction between these two areas would facilitate a new generation of information systems that will be capable of servicing these applications. Although there are researchers in information systems who have addressed themselves to issues of uncertainty, as well as researchers in uncertainty modeling who have considered the pragmatic demands and constraints of information systems, to a large extent there has been only limited interaction between these two areas. As the subtitle, "From Needs to Solutions," indicates, this book presents view points of information systems experts on the needs that challenge the uncer tainty capabilities of present information systems, and it provides a forum to researchers in uncertainty modeling to describe models and systems that can address these needs.


Uncertainty Management in Information Systems

Uncertainty Management in Information Systems

Author: Amihai Motro

Publisher: Springer Science & Business Media

Published: 1996-12-31

Total Pages: 490

ISBN-13: 9780792398035

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Uncertainty Management in Information Systems: From Needs to Solutions is a book about how information systems can be made to manage information permeated with uncertainty. This subject is at the intersection of two areas of knowledge: information systems is an area that concentrates on the design of practical systems that can store and retrieve information; uncertainty modeling is an area in artificial intelligence concerned with accurate representation of uncertain information and with inference and decision-making under conditions infused with uncertainty. The first part of this book describes issues and challenges in the area of imperfect information that confront information systems, and the second part covers the principal theories for modeling imperfect information, and shows how these theories may be adapted to information systems. All chapters are original contributions and present solutions that have been applied and the experiences that have been gained from those solutions. The material has been closely edited by the book's editors for content, consistency and style. This authoritative book is state-of-the-art coverage of `Uncertainty Management in Information Systems'.


Management of Uncertainty

Management of Uncertainty

Author: Gudela Grote

Publisher: Springer Science & Business Media

Published: 2009-09-17

Total Pages: 199

ISBN-13: 1848823738

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As I write, the financial systems of the world are collapsing with still no clear indication of what the consequences will be and which measures should be taken to avoid such a crisis in the future. There seems to be agreement though, that the financial instruments introduced in the past few decades entailed far too much complexity and uncertainty and that there was too little regulatory control over the use of these instruments. Management of uncertainty with the aim of achieving self-control is the core concern of this book. It was not written with a focus on financial systems, but many concepts developed in this book are applicable to this field as well. The - neric principles of reducing, maintaining or increasing uncertainties in view of the different contingencies an organization is faced with, the fundamental issue of how much control is possible and who should be in control, and the question of how much and what kind of regulation is necessary with the overall aim of finding an appropriate balance between system stability and flexibility are at the centre of heated debates on the future of finance.


Scalable Uncertainty Management

Scalable Uncertainty Management

Author: Sergio Greco

Publisher: Springer

Published: 2008-10-01

Total Pages: 411

ISBN-13: 3540879935

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This book constitutes the refereed proceedings of the Second International Conference on Scalable Uncertainty Management, SUM 2008, held in Naples, Italy, in Oktober 2008. The 27 revised full papers presented together with the extended abstracts of 3 invited talks/tutorials were carefully reviewed and selected from 42 submissions. The papers address artificial intelligence researchers, database researchers, and practitioners to demonstrate theoretical techniques required to manage the uncertainty that arises in large scale real world applications and to cope with large volumes of uncertainty and inconsistency in databases, the Web, the semantic Web, and artificial intelligence in general.


Advances in Information Systems

Advances in Information Systems

Author: Tatyana Yakhno

Publisher: Springer

Published: 2003-06-26

Total Pages: 473

ISBN-13: 3540408886

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This volume contains the proceedings of the First International Conference on Advances in Information Systems (ADVIS) held in Izmir (Turkey), 25{27 October, 2000. This conference was dedicated to the memory of Professor Esen Ozkarahan. He was great researcher who made an essential contribution to the development of information systems. This conference was organized by the Computer - gineering Department of Dokuz Eylul University of Izmir. This department was established in 1994 by the founding chairman Professor Ozkarahan and there he worked for the last ve years of his live. The main goal of the conference was to bring together researchers from all around the world working in di erent areas of information systems to share new ideas and to represent their latest results. We received 80 submissions from 30 countries. The Program Committee selected 44 papers for presentation at the conference. The invited and accepted contributions cover a large variety of topics: - neral aspects of information systems, data bases, data warehousing, computer networks, Internet technologies, content-based image retrieval, information - trieval, constraint programming and arti cial intelligence. The success of the conference was dependent upon the hard work of a large number of people. We gratefully acknowledge the members of the Program C- mittee who helped to coordinate the process of refereeing all submitted papers. We also thank all the other specialists who reviewed the papers.


Managing Uncertainty in Expert Systems

Managing Uncertainty in Expert Systems

Author: Jerzy W. Grzymala-Busse

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 242

ISBN-13: 146153982X

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3. Textbook for a course in expert systems,if an emphasis is placed on Chapters 1 to 3 and on a selection of material from Chapters 4 to 7. There is also the option of using an additional commercially available sheU for a programming project. In assigning a programming project, the instructor may use any part of a great variety of books covering many subjects, such as car repair. Instructions for mostofthe "weekend mechanic" books are close stylisticaUy to expert system rules. Contents Chapter 1 gives an introduction to the subject matter; it briefly presents basic concepts, history, and some perspectives ofexpert systems. Then itpresents the architecture of an expert system and explains the stages of building an expert system. The concept of uncertainty in expert systems and the necessity of deal ing with the phenomenon are then presented. The chapter ends with the descrip tion of taxonomy ofexpert systems. Chapter 2 focuses on knowledge representation. Four basic ways to repre sent knowledge in expert systems are presented: first-order logic, production sys tems, semantic nets, and frames. Chapter 3 contains material about knowledge acquisition. Among machine learning techniques, a methodofrule learning from examples is explained in de tail. Then problems ofrule-base verification are discussed. In particular, both consistency and completeness oftherule base are presented.


Approaches for Managing Uncertainty in Learning Management Systems

Approaches for Managing Uncertainty in Learning Management Systems

Author: Nouran M. Radwan

Publisher: Infinite Study

Published:

Total Pages: 10

ISBN-13:

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The notion of uncertainty in expert systems is dealing with vague data, incomplete information, and imprecise knowledge. Different uncertainty types which are imprecision, vagueness, ambiguity, and inconsistence need different handling models. Uncertain knowledge representation and analysis is an essential issue.


Managing Project Uncertainty

Managing Project Uncertainty

Author: David Cleden

Publisher: Routledge

Published: 2017-03-02

Total Pages: 131

ISBN-13: 1351920413

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Dealing effectively with uncertainty requires today's project manager to be familiar with a broad spectrum of strategies, encompassing both 'hard' and 'soft' methods. This theme of unified thinking (i.e. the need to selectively draw upon a wide range of strategies in any given situation) will differentiate the book from its contemporaries. By picking up where traditional risk management techniques begin to fail, it brings together leading-edge thinking from a variety of disciplines and shows how these techniques can be used to conquer uncertainty in projects. The ability to make good decisions when faced with uncertainty is the real challenge. It is a universal truth that a decision is only as good as the information it is based on. But good information is often hard to come by, and all projects are vulnerable to the unknown and the unknowable. Thus, uncertainty becomes the sworn enemy of the project manager. Wherever we try to analyse, quantify, plan and act, uncertainty lies in wait to surprise us with its ambiguity and unpredictability. It lurks in every stage of the project lifecycle: in the planning (how long will this really take?), the initiation (this isn't the situation I expected!), the execution (who could have foreseen that happening?), and even the completion of a project (where are the expected benefits?). But managing uncertainty is a lot more than just applying risk management techniques. It requires a deep appreciation of how uncertainty arises and, by recognising its different guises, the appropriate strategies can be formulated. If we can learn how to reduce uncertainty, we can make better management decisions and increase the chances of the project succeeding. This book addresses five key questions: ¢ Why is there uncertainty in projects? ¢ How do you spot the symptoms of uncertainty, preferably at an early stage? ¢ What can be done to avoid uncertainty? ¢ What strategies can be used to deal with project uncertainty? ¢ How can both the individual and the organisation learn to cope more effectively in the future? The reader is assumed to be a either a project management professional, or a senior manager looking for ways to improve project management strategy within their organisation. As such, a foundation in project management basics is assumed, although not essential. The book then builds on this by exposing new ideas and concepts, and shows how these can be harnessed to tackle uncertainty in its many guises.


Scalable Uncertainty Management

Scalable Uncertainty Management

Author: Eyke Hüllermeier

Publisher: Springer

Published: 2012-09-11

Total Pages: 662

ISBN-13: 3642333621

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This book constitutes the refereed proceedings of the 6th International Conference on Scalable Uncertainty Management, SUM 2012, held in Marburg, Germany, in September 2012. The 41 revised full papers and 13 revised short papers were carefully reviewed and selected from 75 submissions. The papers cover topics in all areas of managing and reasoning with substantial and complex kinds of uncertain, incomplete or inconsistent information including applications in decision support systems, machine learning, negotiation technologies, semantic web applications, search engines, ontology systems, information retrieval, natural language processing, information extraction, image recognition, vision systems, data and text mining, and the consideration of issues such as provenance, trust, heterogeneity, and complexity of data and knowledge.


Scalable Uncertainty Management

Scalable Uncertainty Management

Author: Lluis Godo

Publisher: Springer

Published: 2009-08-29

Total Pages: 318

ISBN-13: 3642043887

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This volume contains the papers presented at the Third International Conference on Scalable Uncertainty Management, SUM 2009, in Washington, DC, September 28-30, 2009. It contains 21 technical papers which were selected out of 30 submitted papers in a rigourous reviewing process. The volume also contains extended abstracts of two invited talks. The volume reflects the growing interest in uncertainty and incosistency and aims at bringing together all those interested in the management of uncertainty and inconsistency at large.