ON DOMINANCE RELATIONS IN DISJUNCTIVE SET-VALUED ORDERED INFORMATION SYSTEMS

2010 ◽  
Vol 09 (01) ◽  
pp. 9-33 ◽  
Author(s):  
Y. H. QIAN ◽  
J. Y. LIANG ◽  
P. SONG ◽  
C. Y. DANG
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Rough Sets ◽  
Semantic Interpretation ◽  
Dominance Relation ◽  
New Approach ◽  
Dominance Relations ◽  
Intelligent Decision Making ◽  
Intelligent Decision

Set-valued information systems are generalized models of single-valued information systems. Its semantic interpretation can be classified into two categories: disjunctive and conjunctive. We focus on the former in this paper. By introducing four types of dominance relations to the disjunctive set-valued information systems, we establish a dominance-based rough sets approach, which is mainly based on the substitution of the indiscernibility relation by the dominance relations. Furthermore, we develop a new approach to sorting for objects in disjunctive set-valued ordered information systems, which is based on the dominance class of an object induced by a dominance relation. Finally, we propose criterion reductions of disjunctive set-valued ordered information systems that eliminate only those information that are not essential from the ordering of objects. The approaches show how to simplify a disjunctive set-valued ordered information system. Throughout this paper, we establish in detail the interrelationships among the four types of dominance relations, which include corresponding dominance classes, rough sets approaches, sorting for objects and criterion reductions. These results give a kind of feasible approaches to intelligent decision making in disjunctive set-valued ordered information systems.

Maintaining Dynamic Information Systems Using Incremental Dominance-Based Rough Set Approach

2014 ◽  
Vol 631-632 ◽  
pp. 53-56
Author(s):  
Yan Li ◽  
Xiao Qing Liu ◽  
Jia Jia Hou
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Rough Set ◽  
Rough Sets ◽  
Dynamic Information ◽  
Knowledge Reduction ◽  
Incremental Approach

Dominance-based rough sets approach (DRSA) is an effective tool to deal with information with preference-ordered attribute domain. In practice, many information systems may evolve when attribute values are changed. Updating set approximations for these dynamic information systems is a necessary step for further knowledge reduction and decision making in DRSA. The purpose of this paper is to present an incremental approach when the information system alters dynamically with the change of condition attribute values. The updating rules are given with proofs, and the experimental evaluations on UCI data show that the incremental approach outperforms the original non-incremental one.

Updated Architectures for the Integration of Decision Making Support Functionalities

2011 ◽  
pp. 3884-3889 ◽  
Author(s):  
Guisseppi A. Forgionne
Keyword(s):  
Decision Making ◽  
Information Systems ◽  
Intelligent Systems ◽  
Data Access ◽  
Robust Decision Making ◽  
Intelligent Support ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
New Literature ◽  
Decision Making Support

Information systems research continues to examine ways to improve support for decision making. The evolution from simple data access and reporting to complex analytical, creative, and artificially intelligent support for decision making persists (Holsapple & Whinston, 1996). In the evolution, existing information systems still, and new intelligent systems have been created to, provide the desired decision making support. By studying the existing, and new, systems’ characteristics, advantages, and disadvantages, researchers and practitioners can better design, develop, and implement robust decision making support systems (Kumar, 1999). The original article facilitated such study by presenting and illustrating the underlying information system architectures for robust decision making support (Forgionne, 2005). This article updates the original by offering additional contributions to the subject. New literature on intelligent decision making support is examined, and the relevant findings are discussed. The title has been modified slightly to reflect the updates.

scholarly journals Approximate Accuracy Approaches to Attribute Reduction for Information Systems

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Deshan Liu ◽  
Dapeng Wang ◽  
Deqin Yan ◽  
Yu Sang
Keyword(s):  
Information System ◽  
Information Systems ◽  
Incomplete Information ◽  
Rough Sets ◽  
Attribute Reduction ◽  
New Approach ◽  
Rough Sets Theory ◽  
Incomplete Information Systems ◽  
Sets Theory ◽  
Novel Algorithm

The key problem for attribute reduction to information systems is how to evaluate the importance of an attribute. The algorithms are challenged by the variety of data forms in information system. Based on rough sets theory we present a new approach to attribute reduction for incomplete information systems and fuzzy valued information systems. In order to evaluate the importance of an attribute effectively, a novel algorithm with rigorous theorem is proposed. Experiments show the effect of proposed algorithm.

Effectivness of Health Information System Applications: Clinical Information and Diagnosis-Treatment Systems in Turkey

2017 ◽  
Vol 5 (1) ◽  
pp. 122
Author(s):  
Assist. Prof. Dr. Demokaan DEMİREL
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Management Information System ◽  
Health Sector ◽  
Health Information System ◽  
Clinical Information ◽  
Clinical Decision ◽  
Clinical Information Systems ◽  
Management Information

The distinctive quality of the new social structure is that information becomes the only factor of production. In today's organizations, public administrators are directly responsible for applying information to administrative processes. In addition to his managerial responsibilities, a knowledge based organization requires every employee to take responsibility for achieving efficiency. This has increased the importance of information systems in the decision-making process. Information systems consist of computer and communication technology, data base management and model management and include activity processing system, management information system, decision support systems, senior management information system, expert systems and office automation systems. Information systems in the health sector aim at the management and provision of preventive and curative health services. The use of information systems in healthcare has the benefits of increasing service quality, shortening treatment processes, maximizing efficiency of the time, labour and medical devices. The use of information systems for clinical decision making and reducing medical errors in the healthcare industry dates back to the 1960s. Clinical information systems involve processing, storing and re-accessing information that supports patient care in a hospital. Clinical information systems are systems that are directly or indirectly related to patient care. These systems include electronic health/patient records, clinical decision support systems, nurse information systems, patient tracking systems, tele-medicine, case mix and smart card applications. Diagnosis-treatment systems are information-based systems used in the diagnosis and treatment of diseases. It consists of laboratory information systems, picture archiving and communication system, pharmacy information system, radiology information system, nuclear medicine information system. This study aims to evaluate the effectiveness of health information system applications in Turkey. The first part of the study focuses on the concept of information systems and the types of information systems in organization structures. In the second part, clinical information systems and applications for diagnosis-treatment systems in Turkey are examined. Finally, the study evaluates applications in the health sector qualitatively from the new organizational structure, which is formed by information systems.

Incremental Approach for Updating Approximations of Variable Precision Rough Set Based on Dominance Relations

2014 ◽  
Vol 631-632 ◽  
pp. 49-52
Author(s):  
Yan Li ◽  
Jia Jia Hou ◽  
Xiao Qing Liu
Keyword(s):  
Information System ◽  
Rough Set ◽  
Dominance Relation ◽  
Incremental Updating ◽  
Dominance Relations ◽  
Incremental Approach ◽  
Variable Precision ◽  
Variable Precision Rough Set ◽  
Over Time

Variable precision rough set (VPRS) based on dominance relation is an extension of traditional rough set by which can handle preference-ordered information flexibly. This paper focuses on the maintenance of approximations in dominance based VPRS when the objects in an information system vary over time. The incremental updating principles are given as inserting or deleting an object, and some experimental evaluations validates the effectiveness of the proposed method.

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