An Intelligent Support System Integrating Data Mining and Online Analytical Processing

2011 ◽  
pp. 141-156
Author(s):  
Rahul Singh ◽  
Richard T. Redmond ◽  
Victoria Yoon
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Makers ◽  
Online Analytical Processing ◽  
Intelligent Decision Making ◽  
Course Of Action ◽  
Intelligent Decision ◽  
Analytical Processing ◽  
Intelligent Decision Support

Intelligent decision support requires flexible, knowledge-driven analysis of data to solve complex decision problems faced by contemporary decision makers. Recently, online analytical processing (OLAP) and data mining have received much attention from researchers and practitioner alike, as components of an intelligent decision support environment. Little that has been done in developing models to integrate the capabilities of data mining and online analytical processing to provide a systematic model for intelligent decision making that allows users to examine multiple views of the data that are generated using knowledge about the environment and the decision problem domain. This paper presents an integrated model in which data mining and online analytical processing complement each other to support intelligent decision making for data rich environments. The integrated approach models system behaviors that are of interest to decision makers; predicts the occurrence of such behaviors; provides support to explain the occurrence of such behaviors and supports decision making to identify a course of action to manage these behaviors.

An Intelligent Support System Integrating Data Mining and Online Analytical Processing

2008 ◽  
pp. 2964-2977
Author(s):  
Rahul Singh ◽  
Richard T. Redmond ◽  
Victoria Yoon
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Makers ◽  
Online Analytical Processing ◽  
Intelligent Decision Making ◽  
Course Of Action ◽  
Intelligent Decision ◽  
Analytical Processing ◽  
Intelligent Decision Support

Intelligent decision support requires flexible, knowledge-driven analysis of data to solve complex decision problems faced by contemporary decision makers. Recently, online analytical processing (OLAP) and data mining have received much attention from researchers and practitioner alike, as components of an intelligent decision support environment. Little that has been done in developing models to integrate the capabilities of data mining and online analytical processing to provide a systematic model for intelligent decision making that allows users to examine multiple views of the data that are generated using knowledge about the environment and the decision problem domain. This paper presents an integrated model in which data mining and online analytical processing complement each other to support intelligent decision making for data rich environments. The integrated approach models system behaviors that are of interest to decision makers; predicts the occurrence of such behaviors; provides support to explain the occurrence of such behaviors and supports decision making to identify a course of action to manage these behaviors.

Improving Intelligent Decision Making in Urban Planning

2021 ◽  
Vol 8 (3) ◽  
pp. 40-58
Author(s):  
Abderrazak Khediri ◽  
Mohamed Ridda Laouar ◽  
Sean B. Eom
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Urban Planning ◽  
Agglomerative Clustering ◽  
New Techniques ◽  
Intelligent Decision Support System ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Urban Issues ◽  
Intelligent Decision Support

Generally, decision making in urban planning has progressively become difficult due to the uncertain, convoluted, and multi-criteria nature of urban issues. Even though there has been a growing interest to this domain, traditional decision support systems are no longer able to effectively support the decision process. This paper aims to elaborate an intelligent decision support system (IDSS) that provides relevant assistance to urban planners in urban projects. This research addresses the use of new techniques that contribute to intelligent decision making: machine learning classifiers, naïve Bayes classifier, and agglomerative clustering. Finally, a prototype is being developed to concretize the proposition.

Adapted Visual Analytics Process for Intelligent Decision-Making: Application in a Medical Context

2020 ◽  
Vol 19 (01) ◽  
pp. 241-282 ◽  
Author(s):  
Hela Ltifi ◽  
Emna Benmohamed ◽  
Christophe Kolski ◽  
Mounir Ben Ayed
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Visual Analytics ◽  
Visual Analysis ◽  
Intelligent Decision Making ◽  
The Past ◽  
Intelligent Decision ◽  
Intelligent Decision Support Systems ◽  
Intelligent Decision Support

The theoretical and practical researches on Visual Analytics for intelligent decision-making tasks have remarkably advanced in the past few years. Intelligent Decision Support Systems (IDSS) introduce effective and efficient paths from raw data to decision by involving visualization and data mining technologies. Data mining-based DSS produces potentially interesting patterns from data. The transition from extracted patterns to knowledge is a delicate task. In this context, we propose to adapt a common visual analytics process for creating a path that enables the user (decision-maker) to automatically explore and visually extract insights by interacting with the patterns. This proposal is inspired from integrating traditional visual analytics concepts with the mental model of knowledge visualization. The idea is to combine an automatic and visual analysis of patterns to generate knowledge for the purpose of decision-making. To validate our proposal, we have applied it to a medical case study for the fight against Nosocomial Infections in Intensive Care Units. The developed platform was evaluated according to the utility and usability dimensions.

A moral analysis of intelligent decision-support systems in diagnostics through the lens of Luciano Floridi’s information ethics

Human Affairs ◽  
2021 ◽  
Vol 31 (2) ◽  
pp. 149-164
Author(s):  
Dmytro Mykhailov
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Medical Diagnosis ◽  
Moral Agency ◽  
Moral Agent ◽  
Well Being ◽  
Medical Diagnostics ◽  
Intelligent Decision ◽  
Luciano Floridi ◽  
Intelligent Decision Support

Abstract Contemporary medical diagnostics has a dynamic moral landscape, which includes a variety of agents, factors, and components. A significant part of this landscape is composed of information technologies that play a vital role in doctors’ decision-making. This paper focuses on the so-called Intelligent Decision-Support System that is widely implemented in the domain of contemporary medical diagnosis. The purpose of this article is twofold. First, I will show that the IDSS may be considered a moral agent in the practice of medicine today. To develop this idea I will introduce the approach to artificial agency provided by Luciano Floridi. Simultaneously, I will situate this approach in the context of contemporary discussions regarding the nature of artificial agency. It is argued here that the IDSS possesses a specific sort of agency, includes several agent features (e.g. autonomy, interactivity, adaptability), and hence, performs an autonomous behavior, which may have a substantial moral impact on the patient’s well-being. It follows that, through the technology of artificial neural networks combined with ‘deep learning’ mechanisms, the IDSS tool achieves a specific sort of independence (autonomy) and may possess a certain type of moral agency. Second, I will provide a conceptual framework for the ethical evaluation of the moral impact that the IDSS may have on the doctor’s decision-making and, consequently, on the patient’s wellbeing. This framework is the Object-Oriented Model of Moral Action developed by Luciano Floridi. Although this model appears in many contemporary discussions in the field of information and computer ethics, it has not yet been applied to the medical domain. This paper addresses this gap and seeks to reveal the hidden potentialities of the OOP model for the field of medical diagnosis.

Integrating OLAP/SOLAP in E-Business Domains

2011 ◽  
Vol 24 (3) ◽  
pp. 45-60
Author(s):  
Ben Ali ◽  
Samar Mouakket
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Data Analysis ◽  
United Arab Emirates ◽  
Decision Makers ◽  
Job Seekers ◽  
Job Market ◽  
Analysis Techniques ◽  
Analytical Processing ◽  
User Friendly

E-business domains have been considered killer domains for different data analysis techniques. Most researchers have examined data mining (DM) techniques to analyze the databases behind E-business websites. DM has shown interesting results, but this technique presents some restrictions concerning the content of the database and the level of expertise of the users interpreting the results. In this paper, the authors show that successful and more sophisticated results can be obtained using other analysis techniques, such as Online Analytical Processing (OLAP) and Spatial OLAP (SOLAP). Thus, the authors propose a framework that fuses or integrates OLAP with SOLAP techniques in an E-business domain to perform easier and more user-friendly data analysis (non-spatial and spatial) and improve decision making. In addition, the authors apply the framework to an E-business website related to online job seekers in the United Arab Emirates (UAE). The results can be used effectively by decision makers to make crucial decisions in the job market of the UAE.

Intelligent Decision Support System in Damage Control of Damaged Ship

2013 ◽  
Vol 694-697 ◽  
pp. 2476-2482
Author(s):  
Ang Li ◽  
Jin Yun Pu
Keyword(s):  
Data Mining ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Damage Control ◽  
Model Management ◽  
Intelligent Decision Support System ◽  
Intelligent Decision ◽  
Intelligent Decision Support ◽  
Damaged Ship

An intelligent decision support system in damage control of damaged ship combined with data mining is constructed in this paper. The human-computer interaction subsystem, the database management subsystem, the model management subsystem and the knowledge management subsystem are introduced in detail and some programming technologies of the system are displayed. The pivotal technology of the realization of this system is discussed briefly at last.

Based on the Agent of the Intelligent Decision Support System Research

2012 ◽  
Vol 482-484 ◽  
pp. 237-240
Author(s):  
Rui Feng Wang ◽  
Peng Li
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Rapid Development ◽  
Agent Technology ◽  
System Research ◽  
Intelligent Decision Support System ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Intelligent Decision Support

With the rapid development of Agent technology, its application field, more and more widely. In this paper, a based on the Agent of the intelligent decision support system frame, that is, in the original decision support system based on building an Agent, thus increasing the DSS of intelligent decision making level, for the future of intelligent decision support system provides a new way of thinking.

Sign in / Sign up

Export Citation Format

Share Document