Context-Driven Decision Mining

View Sample PDF

Author(s): Alexander mirnov (Institution of the Russian Academy of Sciences, St. Petersburg Institute for Informatics and Automation RAS, Russia)
Copyright: 2009
Pages: 8
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch051

Purchase

View Context-Driven Decision Mining on the publisher's website for pricing and purchasing information.

Abstract

Decisions in the modern world are often made in rapidly changing, sometimes unexpected, situations. Such situations require availability of systems / tools allowing fast and clear description of situation, generation of new and reuse of previously made effective solutions for situation reformation, selection of a right decision maker and supplying him/her with necessary data. Such tools include components for actual situation description, user modeling, finding appropriate methods for problem solving, integration of data from heterogeneous sources, finding / generation of insufficient data, removing uncertainties, estimating solutions, etc. During decision making process a large amount of auxiliary raw data are accumulated in repositories. Methods of data mining are used in such systems for different purposes: finding associative rules between decisions and factors affecting them, user clustering using decision trees and neural networks, recognition of common users’ features / interests and others (Chiang et al., 2006; Li, 2005; Thomassey and Fiordaliso, 2006). Validation of the obtained results can be performed using simulation software modules.

The IRMA Community

Research IRM

Context-Driven Decision Mining

Purchase

Abstract

Related Content

IRMA Sponsors