Decision and Inhibitory Trees and Rules for Decision Tables with Many-valued Decisions


Book Description

The results presented here (including the assessment of a new tool – inhibitory trees) offer valuable tools for researchers in the areas of data mining, knowledge discovery, and machine learning, especially those whose work involves decision tables with many-valued decisions. The authors consider various examples of problems and corresponding decision tables with many-valued decisions, discuss the difference between decision and inhibitory trees and rules, and develop tools for their analysis and design. Applications include the study of totally optimal (optimal in relation to a number of criteria simultaneously) decision and inhibitory trees and rules; the comparison of greedy heuristics for tree and rule construction as single-criterion and bi-criteria optimization algorithms; and the development of a restricted multi-pruning approach used in classification and knowledge representation.




The Decision Model


Book Description

In the current fast-paced and constantly changing business environment, it is more important than ever for organizations to be agile, monitor business performance, and meet with increasingly stringent compliance requirements. Written by pioneering consultants and bestselling authors with track records of international success, The Decision Model: A




Balancing Agility and Formalism in Software Engineering


Book Description

This book constitutes the thoroughly refereed post-conference proceedings of the Second IFIP TC 2 Central and East Conference on Software Engineering Techniques, CEE-SET 2007, held in Poznan, Poland, in October 2007. The 21 revised full papers presented together with 2 keynote addresses were carefully reviewed and selected from 73 initial submissions. The papers are organized in topical sections on measurement, processes, UML, experiments, tools, and change.




Modeling Decisions for Artificial Intelligence


Book Description

This volume contains papers presented at the 7th International Conference on Modeling Decisions for Arti?cial Intelligence (MDAI 2010), held in Perpignan, France, October 27–29. This conference followed MDAI 2004 (Barcelona, C- alonia, Spain), MDAI 2005 (Tsukuba, Japan), MDAI 2006 (Tarragona, Cata- nia, Spain), MDAI 2007 (Kitakyushu, Japan), MDAI 2008 (Sabadell, Catalonia, Spain), and MDAI 2009 (Awaji Island, Japan) with proceedings also published in the LNAI series (Vols. 3131, 3558, 3885, 4617, 5285, and 5861). The aim of this conference was to provide a forum for researchers to discuss theory and tools for modeling decisions, as well as applications that encompass decision-making processes and information fusion techniques. The organizers received 43 papers from 12 di?erent countries, from Europe, Asia, Australia and Africa, 25 of which are published in this volume. Each s- mission received at least two reviews from the Program Committee and a few externalreviewers.Wewouldliketoexpressourgratitudetothemfortheirwork. The plenary talks presented at the conference are also included in this volume. TheconferencewassupportedbytheCNRS:CentreNationaldelaRecherche Scienti?que,theUniversit´ edePerpignanVia Domitia,theELIAUS:Laboratoire Electronique Informatique Automatique Syst` emes, IMERIR: Ecole d'Ing´ enierie Informatique et Robotique, the UNESCO Chair in Data Privacy, the Japan - cietyforFuzzyTheoryandIntelligentInformatics(SOFT),theCatalanAssoc- tionfor Arti?cialIntelligence(ACIA), the EuropeanSociety for Fuzzy Logicand Technology(EUSFLAT), the Spanish MEC(ARES—CONSOLIDER INGENIO 2010 CSD2007-00004).




Guide to Advanced Software Testing


Book Description

A guide to advanced testing -- Basic aspects of software testing -- Testing processes -- Test management -- Test techniques -- Testing of software characteristics -- Reviews (static testing) -- Incident management -- Standards and test improvement process -- Testing tools and automation -- People skills.




Logical Foundations for Rule-Based Systems


Book Description

The book presents logical foundations for rule-based systems. An attempt has been made to provide an in-depth discussion of logical and other aspects of such systems, including languages for knowledge representation, inference mechanisms, inference control, design and verification. The ultimate goal was to provide a deeper theoretical insight into the nature of rule-based systems and put together the most complete presentation including details so frequently skipped in typical textbooks. The book may be useful to potentially wide audience, but it is aimed at providing specific knowledge for graduate, post-graduate and Ph.D. students, as well as knowledge engineers and research workers involved in the domain of AI. It also constitutes a summary of the Author’s research and experience gathered through several years of his research work.




Transactions on Rough Sets I


Book Description

The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, starting from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. This first volume of the Transactions on Rough Sets opens with an introductory article by Zdzislaw Pawlak, the originator of rough sets. Nine papers deal with rough set theory and eight are devoted to applications in various domains.




NBS Technical Note


Book Description







Transactions on Rough Sets XII


Book Description

The LNCS journal Transactions on Rough Sets is devoted to the entire spectrum of rough sets related issues, from logical and mathematical foundations, through all aspects of rough set theory and its applications, such as data mining, knowledge discovery, and intelligent information processing, to relations between rough sets and other approaches to uncertainty, vagueness, and incompleteness, such as fuzzy sets and theory of evidence. This volume contains 8 revised selected papers from 11 submissions to the Rough Set and Knowledge Technology Conference (RSKT 2008), together with 5 papers introducing advances in rough set theory and its applications. The topics covered are: perceptually near Pawlak partitions, hypertext classification, topological space versus rough set theory in terms of lattice theory, feature extraction in interval-valued information systems, jumping emerging patterns (JEP), and rough set theory.