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作者： Nguyen, Dang Nguyen, Loan T.T. Vo, Bay Pedrycz, Witold Division of Data Science Ton Duc Thang University Ho Chi Minh City Viet Nam Division of Knowledge and System Engineering for ICT Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ho Chi Minh City University of Technology Viet Nam College of Electronics and Information Engineering Sejong University Seoul Korea Republic of Department of Electrical and Computer Engineering University of Alberta EdmontonABT6R 2V4 Canada Department of Electrical and Computer Engineering Faculty of Engineering King Abdulaziz University Jeddah21589 Saudi Arabia Systems Research Institute Polish Academy of Sciences Warsaw Poland

Mining class association rules (CARs) with the itemset constraint is concerned with the discovery of rules, which contain a set of specific items in the rule antecedent and a class label in the rule consequent. This task is commonly encountered in mining medical data. For example, when classifying which section of the population is at high risk for the HIV infection, epidemiologists often concentrate on rules which include demographic information such as gender, age, and marital status in the rule antecedent, and HIV-Positive in the rule consequent. There are two naive strategies to solve this problem, namely pre-processing and post-processing. The post-processing methods have to generate and consider a huge number of candidate CARs while the performance of the pre-processing methods depend on the number of records filtered out. Therefore, such approaches are time consuming. This study proposes an efficient method for mining CARs with the itemset constraint based on a lattice structure and the difference between two sets of object identifiers (diffset). Firstly, a lattice structure is built to store all frequent itemsets in the dataset. To reduce memory usage, instead of the entire set of object identifiers, the diffset is used. Secondly, the lattice is traversed to generate only rules which satisfy the itemset constraint. The experimental results show that the proposed algorithm outperforms existing methods in terms of both the mining time and memory usage. © 2016 Elsevier B.V. All rights reserved.

关键词： Data mining

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Toward evaluating the level of crowd wisdom using interval estimates

Toward evaluating the level of crowd wisdom using interval e...

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作者： Nguyen, Van Du Truong, Hai Bang Merayo, Mercedes G. Nguyen, Ngoc Thanh Division of Knowledge and System Engineering for ICT Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Viet Nam Department Sistemas Informáticos y Computación Universidad Complutense de Madrid Spain Faculty of Computer Science and Management Wroclaw University of Science and Technology Wyb. Wyspianskiego 27 Wroclaw50-370 Poland Faculty of Information Technology Nguyen Tat Thanh University Ho Chi Minh city Viet Nam

Recently, the use of the wisdom of crowds (WoC) for finding solutions to a wide range of real-life problems has dramatically expanded. Prior studies have revealed that diversity, independence, decentralization, and aggregation are the determinants of collective wisdom. However, these findings are often based on the so-called point estimates - single values are used as the representations of individual predictions on the task of estimating unknown quantities or predicting outcomes of future events. In some situations, interval values, which are often called interval estimates, can be used for such representations. Accordingly, one can provide an individual prediction in the form of an interval value including a lower and an upper bounds. Taking into account this kind of representation, in this paper, we present a case study in which collectives of randomly selected predictions can outperform those of most accurate predictions. Then, we evaluate the WoC level by taking into account diversity and cardinality. The computational experiments have indicated that diversity is positively related to collective wisdom. Finally, we discuss some related theoretical and practical implications for further research. © 2019 - IOS Press and the authors. All rights reserved.

关键词： Forecasting

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Correction to: Equilibrium customer behavior in the M/M/1 retrial queue with working vacations and a constant retrial rate

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Operational Research 2019年第2期20卷 647-647页

作者： Do, Nam H. Van Do, Tien Melikov, Agassi Division of Knowledge and System Engineering for ICT (KSE-ICT) Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Vietnam Analysis Design and Development of ICT Systems (AddICT) Laboratory Department of Networked Systems and Services Budapest University of Technology and Economics Budapest Hungary Institute of Cybernetics National Academy of Sciences of Azerbaijan Baku Azerbaijan

In the originally published article, the order of the affiliations of the first and the corresponding author was incorrectly indicated.

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Corrigendum to “Modelling opportunistic spectrum renting in mobile cellular networks” [J. Netw. Comput. Appl. 52 (2015) 129–138]

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Journal of Network and Computer Applications 2016年 73卷 98-98页

作者： Tien Van Do Nam H. Do Ádám Horváth Jinting Wang Division of Knowledge and System Engineering for ICT (KSE-ICT) Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Analysis Design and Development of ICT Systems (AddICT) Laboratory Budapest University of Technology and Economics H-1117 Magyar tudósok körútja 2 Budapest Hungary Faculty of Informatics University of Debrecen Egyetem tér 1 PO Box 12 4010 Debrecen Hungary Institute of Informatics and Economics University of West Hungary Bajcsy-Zsilinszky u. 9. Sopron Hungary Department of Mathematics School of Science Beijing Jiaotong University Beijing 100044 China

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