Rule Acquisition Based on Inconsistent Decision-Making Information System

2013 ◽  
Vol 411-414 ◽  
pp. 1975-1978
Author(s):  
De Xing Wang ◽  
Hong Yan Lu ◽  
Hong Wei Lu
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Rough Set Theory ◽  
Decision Rules ◽  
Knowledge Reduction ◽  
Inconsistent Information ◽  
Rule Acquisition ◽  
Theory Application ◽  
Rules Acquisition

Rule acquisition is a hot topic in the field of data mining. And the inconsistent information systems are widespread nowadays. However, rules acquisition methods are always the difficulty of rough set theory application in inconsistent decision information systems; So the paper proposes a new rule acquisition method. Firstly, we use maximum distribution reduction method for knowledge reduction in single decision-making inconsistent information system and then we use decision-making resolution matrix and decision-making matrix function to get the decision rules. Finally, we mine the rules from inconsistent decision-making information systems.

THE ALGORITHM ON KNOWLEDGE REDUCTION IN INCOMPLETE INFORMATION SYSTEMS

2002 ◽  
Vol 10 (01) ◽  
pp. 95-103 ◽  
Author(s):  
JIYE LIANG ◽  
ZONGBEN XU
Keyword(s):  
Information System ◽  
Information Systems ◽  
Incomplete Information ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Np Hard ◽  
Knowledge Reduction ◽  
Np Hard Problem ◽  
Incomplete Information Systems

Rough set theory is emerging as a powerful tool for reasoning about data, knowledge reduction is one of the important topics in the research on rough set theory. It has been proven that finding the minimal reduct of an information system is a NP-hard problem, so is finding the minimal reduct of an incomplete information system. Main reason of causing NP-hard is combination problem of attributes. In this paper, knowledge reduction is defined from the view of information, a heuristic algorithm based on rough entropy for knowledge reduction is proposed in incomplete information systems, the time complexity of this algorithm is O(|A|2|U|). An illustrative example is provided that shows the application potential of the algorithm.

scholarly journals Decision Rules Acquisition for Inconsistent Disjunctive Set-Valued Ordered Decision Information Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hongkai Wang ◽  
Yanyong Guan ◽  
Jilin Huang ◽  
Jianting Shen
Keyword(s):  
Information System ◽  
Decision Support ◽  
Information Systems ◽  
Decision Support Systems ◽  
Support Systems ◽  
Decision Rules ◽  
Optimal Decision ◽  
Formal Framework ◽  
Rules Acquisition

Set-valued information system is an important formal framework for the development of decision support systems. We focus on the decision rules acquisition for the inconsistent disjunctive set-valued ordered decision information system in this paper. In order to derive optimal decision rules for an inconsistent disjunctive set-valued ordered decision information system, we define the concept of reduct of an object. By constructing the dominance discernibility function for an object, we compute reducts of the object via utilizing Boolean reasoning techniques, and then the corresponding optimal decision rules are induced. Finally, we discuss the certain reduct of the inconsistent disjunctive set-valued ordered decision information system, which can be used to simplify all certain decision rules as much as possible.

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.

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.

scholarly journals PAKKADES.ID UNTUK MENDUKUNG PHYSICAL DISTANCING SAAT MUSYAWARAH ANGGARAN PEMBANGUNAN DESA SEBAGAI UPAYA MENGHADAPI PANDEMI

2020 ◽  
Vol 1 (4) ◽  
pp. 589-595
Author(s):  
Trias Bratakusuma
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Community Participation ◽  
Decision Process ◽  
Speed Up ◽  
Village Government ◽  
Process Decision

Nowadays, although the pageraji village government has implemented e-government but more to increase services through the elimination of the old and complicated bureaukasi structure. In this case more information systems are used to speed up and automate processes. There is no information system yet focused on supporting the decision process. Pakkades.id is a type of information system intended to facilitate budgeting mechanisms. In the process of drafting village development budgets, community participation or aspirations are urgently needed. However, there are often obstacles to getting aspirations from the community because the mechanism that is implemented now only through deliberations implemented one day, this will narrow the reach. Therefore, with the implementation of Pakkades.id which is the result of the study authors of the Funding Ristek Dikti 2019 is expected to efficiency and effectively process decision making through the process of capturing the aspirations of the community better.  

Information Systems

2015 ◽  
pp. 78-108
Keyword(s):  
Decision Making ◽  
Information System ◽  
Information Systems ◽  
Small Business ◽  
Business Manager ◽  
Business Decision ◽  
External Organization ◽  
Support Decision Making

An information system translates data into information to support business decision making. Data, raw unorganized facts, are gathered relative to a business event. The resulting information, which has meaning in the hands of a user, must be complete and accurate in order to support timely decision making. The acquisition of an information system by a small business will be a relatively costly endeavour. The small business manager will tend to rely upon an internal individual or external organization for advice when acquiring an information system. Further, the information system will be employed to improve the efficiency of daily operations of a small business. This chapter describes information systems. In general, an information system turns data into information to support decision making. The information must be timely, complete, and accurate relative to the decisions which must be made.

On Quasi Discrete Topological Spaces in Information Systems

2012 ◽  
Vol 3 (2) ◽  
pp. 38-52 ◽  
Author(s):  
Tutut Herawan
Keyword(s):  
Information System ◽  
Information Systems ◽  
Topological Space ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Topological Spaces ◽  
Discrete Topology

This paper presents an alternative way for constructing a topological space in an information system. Rough set theory for reasoning about data in information systems is used to construct the topology. Using the concept of an indiscernibility relation in rough set theory, it is shown that the topology constructed is a quasi-discrete topology. Furthermore, the dependency of attributes is applied for defining finer topology and further characterizing the roughness property of a set. Meanwhile, the notions of base and sub-base of the topology are applied to find attributes reduction and degree of rough membership, respectively.

Applied Rough Set Logics for Multi-Criteria Decision Analysis in Stock Index Volatility Projection

2011 ◽  
Vol 14 (04) ◽  
pp. 715-735
Author(s):  
Wen-Rong Jerry Ho
Keyword(s):  
Decision Making ◽  
Set Theory ◽  
Rough Set ◽  
Rough Set Theory ◽  
Decision Rules ◽  
Multiple Criteria Decision Making ◽  
Stock Index ◽  
Rule Based ◽  
Set Up ◽  
Decision Making Model

The main purpose of this paper is to advocate a rule-based forecasting technique for anticipating stock index volatility. This paper intends to set up a stock index indicators projection prototype by using a multiple criteria decision making model consisting of the cluster analysis (CA) technique and Rough Set Theory (RST) to select the important attributes and forecast TSEC Capitalization Weighted Stock Index. The projection prototype was then released to forecast the stock index in the first half of 2009 with an accuracy of 66.67%. The results point out that the decision rules were authenticated to employ in forecasting the stock index volatility appropriately.

ON KNOWLEDGE REDUCTION IN INCONSISTENT DECISION INFORMATION SYSTEMS

2004 ◽  
Vol 12 (05) ◽  
pp. 651-672 ◽  
Author(s):  
DEYU LI ◽  
BO ZHANG ◽  
YEE LEUNG
Keyword(s):  
Information Systems ◽  
Decision Rules ◽  
Compact Representation ◽  
Knowledge Reduction ◽  
Types Of Knowledge ◽  
Prediction Capability

Due to issues such as noise in data, compact representation and prediction capability, many types of knowledge reduction and decision rules have been proposed and applied in inconsistent decision information systems. It is thus important to clarify the interrelationships among the existing types of knowledge reduction. In this paper, the relationships, particularly those suggested in [1], are reconsidered and rectified, and some related results are theoretically improved. In terms of two new types of reducts proposed in this paper together with other existing ones, the method for optimizing all types of decision rules is also discussed in details.

scholarly journals Fuzzy Set-Valued Information Systems and the Algorithm of Filling Missing Values for Incomplete Information Systems

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Zhaohao Wang ◽  
Xiaoping Zhang
Keyword(s):  
Information System ◽  
Information Systems ◽  
Incomplete Information ◽  
Rough Set ◽  
Fuzzy Set ◽  
Missing Values ◽  
Rough Set Theory ◽  
Similarity Measures ◽  
New Information ◽  
Incomplete Information Systems

How to effectively deal with missing values in incomplete information systems (IISs) according to the research target is still a key issue for investigating IISs. If the missing values in IISs are not handled properly, they will destroy the internal connection of data and reduce the efficiency of data usage. In this paper, in order to establish effective methods for filling missing values, we propose a new information system, namely, a fuzzy set-valued information system (FSvIS). By means of the similarity measures of fuzzy sets, we obtain several binary relations in FSvISs, and we investigate the relationship among them. This is a foundation for the researches on FSvISs in terms of rough set approach. Then, we provide an algorithm to fill the missing values in IISs with fuzzy set values. In fact, this algorithm can transform an IIS into an FSvIS. Furthermore, we also construct an algorithm to fill the missing values in IISs with set values (or real values). The effectiveness of these algorithms is analyzed. The results showed that the proposed algorithms achieve higher correct rate than traditional algorithms, and they have good stability. Finally, we discuss the importance of these algorithms for investigating IISs from the viewpoint of rough set theory.

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