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An Advanced Stochastic Risk Assessment Approach Proposal Based on KEMIRA-M, QFD and Fine–Kinney Hybridization Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2021-01-23 Gülin Feryal Can; Pelin Toktaş
In this study, an advanced stochastic risk assessment approach based on integration of advanced version of quality function deployment (AV-QFD) and Modified Kemeny Median Indicator Rank Accordance (KEMIRA-M) is proposed. It is aimed to perform a new criterion weighting procedure based on four different distributions as uniform, symmetric triangular, left asymmetric triangular, right asymmetric triangular
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Analysis of Collaboration Evolution in AHP Research: 1982–2018 Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2021-01-21 Dejian Yu; Gang Kou; Zeshui Xu; Shunshun Shi
Bibliometric analysis is effective for evaluating the merits of a given discipline. This study provides an analysis of collaboration evolution in analytic hierarchy process (AHP) research from 1982 to 2018. As an important developed approach of AHP, analytic network process (ANP) is also considered in this review. 9859 publications are harvested from Web of Science to conduct this bibliometric analysis
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Culturally Inclusive Adaptive User Interface (CIAUI) Framework: Exploration of Plasticity of User Interface Design Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2021-01-19 Mahdi H. Miraz; Peter S. Excell; Maaruf Ali
This paper presents a Culturally Inclusive Adaptive User Interface (CIAUI) Framework for developing Mobile Learning (M-Learning) and other mobile applications. The CIAUI Framework specifically incorporates the concepts of universal design aimed for culturally diverse users. This was derived as an outcome of a research project involving the design, analysis and evaluation of artificial intelligence
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A Multiple Attribute Decision-Making Method Based On Free Double Hierarchy Hesitant Fuzzy Linguistic Information Considering the Prioritized and Interactive Attributes Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2021-01-19 Peide liu; Mengjiao Shen; Fei Teng; Baoying Zhu; Lili Rong
As the development and extension of hesitant fuzzy linguistic term sets (HFLTSs), free double hierarchy hesitant fuzzy linguistic term sets (FDHHFLTSs) can describe the evaluation information in more detail. In addition, in practical multiple attribute decision-making (MADM) problems, priority relations and interaction relations usually exist among attributes, and the prioritized interactive Choquet
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Data-Driven Evidential Reasoning Method for Evaluating e-Government Performance Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2021-01-19 Ying Yang; Rui-Xue Lu; Min Xue; Zhi-Qin Shou; Jian-Bo Yang; Lei Fu
The construction of electronic government (e-government) systems is a process of continuous improvement. It is necessary to evaluate the performance of e-government systems regularly to improve the services provided by government agencies and enhance the exchange of information between governments and citizens. Evaluating e-government performance based on citizens’ experience is a multiple criterion
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A New Interactive Algorithm for Continuous Multiple Criteria Problems: A Portfolio Optimization Example Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2021-01-18 Gülşah Karakaya; Ceren Tuncer Şakar
In continuous multiple criteria problems, finding a distinct preferred solution for a decision maker (DM) is not straightforward. There are few recent studies proposed for this task, and the algorithms developed are cognitively difficult and complex for the DM in general. We propose a novel interactive algorithm to guide the DM in converging highly-preferred solutions in continuous multiple criteria
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EWNStream+: Effective and Real-time Clustering of Short Text Streams Using Evolutionary Word Relation Network Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2021-01-18 Shuiqiao Yang; Guangyan Huang; Xiangmin Zhou; Vicky Mak; John Yearwood
The real-time clustering of short text streams has various applications, such as event tracking, text summarization and sentimental analysis. However, accurately and efficiently clustering short text streams is challenging due to the sparsity problem (i.e., the limited information comprised in a single short text document leads to high-dimensional and sparse vectors when we represent short texts using
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ABX-LEX: An Argument-Driven Approach for the Digital Facilitation of Efficient Group Decisions Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2021-01-13 Graham Horton; Jana Goers
The quality of a group decision depends on its members sharing and adopting their various perspectives. Multi-criteria models provide an appropriate vehicle for managing this information sharing because they break down the decision into small, single-issue questions that can be treated independently. We present a new lexicographic decision method with three equivalence classes for use by a group. Our
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Opinions and Actions Dynamics Under Bounded Confidence Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2021-01-09 Min Zhan; Haiming Liang; Can Zhu; Yucheng Dong
Psychologically, agents always like to consider similar opinions. Moreover, in real opinion dynamics, people’s opinions usually influence their actions. Therefore, inspired by the HK bounded confidence model, and continuous opinions and discrete action model, in this paper, we propose opinions and actions dynamics model under bounded confidence to investigate the evolution of opinions and actions in
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Eigensolutions of Partially Reliable Decision Preferences Described by Matrices of Z-Numbers Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-10-09 Rafik A. Aliev; Witold Pedrycz; Oleg H. Huseynov; Rafig R. Aliyev
Eigenvalues and eigenvectors are widely used in various applications. Particularly, these concepts underlie analysis of consistency of a decision maker’s (DMs) preference knowledge. In real-world problems, DMs knowledge is inherently associated with imprecision and partial reliability. This involves combination of fuzzy and probabilistic information. The concept of a Z-number is a formal construct
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A Fuzzy Cognitive Mapping Approach to the Conference Selection Problem Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-10-05 Cigdem Kadaifci; Umut Asan; Y. Ilker Topcu
Academic conferences are popular platforms for academicians to share their research with colleagues, get feedback, and stay up to date on recent academic studies. Conferences also provide opportunities for the participants to express themselves, expand their network, and become socialized. However, academicians are forced to choose a limited number of conferences to participate due to several different
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A Hybrid Fuzzy Multi-Criteria Decision-Making Model to Evaluate the Overall Performance of Public Emergency Departments: A Case Study Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-10-05 Miguel Ortiz-Barrios; Juan-Jose Alfaro-Saiz
Performance evaluation is relevant for supporting managerial decisions related to the improvement of public emergency departments (EDs). As different criteria from ED context and several alternatives need to be considered, selecting a suitable Multicriteria Decision-Making (MCDM) approach has become a crucial step for ED performance evaluation. Although some methodologies have been proposed to address
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Critical Success Factors for Blockchain Technology Adoption in Freight Transportation Using Fuzzy ANP–Modified TISM Approach Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-10-09 Vipulesh Shardeo; Anchal Patil; Jitender Madaan
The dynamic and uncertain demand forces organizations to provide flexible services in order to fulfill customer demands. Freight transportation, being the key component of the businesses, requires adoption of efficient Information and Communication Technologies which can induce transparent and flexible services. Blockchain Technology (BT) is an emerging technology which has great potential to cater
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A New Energy-Efficient Multipath Routing in Internet of Things Based on Gray Theory Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-10-22 Rogayye Khaleghnasab; Karamollah Bagherifard; Samad Nejatian; Hamid Parvin; Bahman Ravaei
Internet of Things (IoT) is a network of smart things. It indicates the ability that the mentioned physical things transfer information with each other. The characteristics of these networks, such as topology dynamicity and energy constraint, make the routing problem a challenging task in these networks. Traditional routing methods could not achieve the required performance in these networks. Therefore
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Review of the Research Landscape of Multi-Criteria Evaluation and Benchmarking Processes for Many-Objective Optimization Methods: Coherent Taxonomy, Challenges and Recommended Solution Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-10-17 R. T. Mohammed; R. Yaakob; A. A. Zaidan; N. M. Sharef; R. H. Abdullah; B. B. Zaidan; K. A. Dawood
Evaluation and benchmarking of many-objective optimization (MaOO) methods are complicated. The rapid development of new optimization algorithms for solving problems with many objectives has increased the necessity of developing performance indicators or metrics for evaluating the performance quality and comparing the competing optimization algorithms fairly. Further investigations are required to highlight
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A Systematic Literature Review for Personnel Scheduling Problems Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-10-17 Emir Hüseyin Özder; Evrencan Özcan; Tamer Eren
Organizations need to focus on many parameters to reach their goals such as personnel satisfaction at the top level, profit maximization, increasing system efficiency and minimizing costs. By carefully examining the significant effect of personnel scheduling on the production of goods and services, achieving a fair distribution of work among the employees paves the way for higher motivation and performance
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Bi-Objective Optimization of Service-Oriented Location-Pricing Model Using Electromagnetism-Like Mechanism Algorithm Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-10-12 Alireza Alinezhad; Vahid Hajipour; Sanaz Hosseinzadeh
This paper develops a multi-objective multi-layer location-pricing (MLLP) model with congested facilities in which the facilities act like a classic queuing system. The customers who arrive to this system receive service at all layers in a predetermined order to fulfill their demands. The goal is to determine (1) optimal number of the facilities required at each layer, (2) optimal allocation of customers
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Constructing an Efficient Machine Learning Model for Tornado Prediction Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-08-31 Fuad Aleskerov; Sergey Demin; Michael B. Richman; Sergey Shvydun; Theodore B. Trafalis; Vyacheslav Yakuba
Tornado prediction variables are analyzed using machine learning and decision analysis techniques. A model based on several choice procedures and the superposition principle is applied for different methods of data analysis. The constructed model has been tested on a database of tornadic events. It is shown that the tornado prediction model developed herein is more efficient than a previous set of
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An Invasive Weed Optimization-Based Fuzzy Decision-making Framework for Bridge Intervention Prioritization in Element and Network Levels Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-08-26 Eslam Mohammed Abdelkader; Mohamed Marzouk; Tarek Zayed
Recently, the number of deteriorating bridges has drastically increased. Furthermore, tight maintenance budgets are cut down, imposing escalating adverse implications on the safety of bridges. This state of affairs entails the development of decision support systems for the effective management of bridges within the allocated budget. As such, this study introduces an invasive weed optimization-based
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Multi-Biological Laboratory Examination Framework for the Prioritization of Patients with COVID-19 Based on Integrated AHP and Group VIKOR Methods Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-08-24 A. S. Albahri; Jameel R. Al-Obaidi; A. A. Zaidan; O. S. Albahri; Rula A. Hamid; B. B. Zaidan; A. H. Alamoodi; M. Hashim
Coronavirus disease (COVID-19) pandemic has a tremendous effect on people’s lives worldwide, and the number of infected patients increases daily. The healthcare sector is affected by a large number of patients with COVID-19, and a solution is urgently needed to avert the risk of deteriorating patients in terms of prioritizing patients based on their health conditions. Prioritization of patients with
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Novel Stable Approach with Probability Distribution for Multi-Criteria Decision-Making Problems of Multi-Valued Neutrosophic Sets Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-08-24 Xu Libo; Li Xingsen; Cui Honglei
In this paper, a novel approach and framework based on interval-dependent degree and probability distribution for multi-criteria decision-making problems with multi-valued neutrosophic sets (MVNSs) is proposed. First, a simplified dependent function and distribution function are given and integrated into a concise formula, which is called the interval-dependent function and contains interval computing
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An Integrated Decision-Making Framework to Appraise Water Losses in Municipal Water Systems Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-08-19 Shaher H. Zyoud; Daniela Fuchs-Hanusch
To mitigate the acute water shortage problems, water utilities are combating to find potential solutions. Water losses management in Water Supply Networks (WSNs) is amongst the prominent solutions. This work intends to develop a decision support framework to diagnose the criticality of WSNs according to an associated Water Loss Risk Index (WLRI) at pipe and zone levels. It utilized the Fuzzy Analytic
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Integrating Risk into Project Control Using Bayesian Networks Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-08-21 Erhan Pişirir; Yasemin Sü; Barbaros Yet
Projects are, by definition, risky and uncertain ventures. Therefore, the performance and risk of major projects should be carefully controlled in order to increase their probability of success. Quantitative project control techniques assist project managers in detecting problems, thus responding to them early on, by comparing the baseline plan with the project progress. However, project risk and uncertainty
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An Improved MABAC Group Decision-Making Method Using Regret Theory and Likelihood in Probability Multi-Valued Neutrosophic Sets Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-08-21 Peide Liu; Shufeng Cheng
Probability multi-valued neutrosophic set (PMVNS) is a preferable tool to capture the preference and hesitancy of decision makers (DMs) and to depict inconsistent and ambiguous information. In this paper, we improve the multi-attributive border approximation area comparison (MABAC) method under the PMVNS environment and establish a three-phase multi-attribute group decision-making (MAGDM) method. Firstly
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ReS-Algorithm for Converting Normalized Values of Cost Criteria Into Benefit Criteria in MCDM Tasks Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-08-26 Irik Z. Mukhametzyanov
A review of modern methods of data normalization in the tasks of multicriteria decision-making and multidimensional classification is presented. The invariant properties of linear normalization methods are determined. Two basic principles of normalization of multidimensional data are defined: preservation of dispositions of natural and normalized values on the measurement scale and the absence of a
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A New Adaptive Weighted Deep Forest and Its Modifications Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-07-22 Lev V. Utkin; Andrei V. Konstantinov; Viacheslav S. Chukanov; Anna A. Meldo
A new adaptive weighted deep forest algorithm which can be viewed as a modification of the confidence screening mechanism is proposed. The main idea underlying the algorithm is based on adaptive weigting of every training instance at each cascade level of the deep forest. The confidence screening mechanism for the deep forest proposed by Pang et al., strictly removes instances from training and testing
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Optimal Key Generation for Data Sanitization and Restoration of Cloud Data: Future of Financial Cyber Security Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-07-23 B. Balashunmugaraja; T. R. Ganeshbabu
Cloud security in finance is considered as the key importance, taking account of the aspect of critical data stored over cloud spaces within organizations all around the globe. They are chiefly relying on cloud computing to accelerate their business profitability and scale up their business processes with enhanced productivity coming through flexible work environments offered in cloud-run working systems
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Hybrid Gaussian Process Inference Model for Construction Management Decision Making Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-07-17 Min-Yuan Cheng; Yu-Wei Wu; Chin-Chi Huang
Construction decision-making often involves several indefinite factors, and wrong decisions usually lead to many losses and may even cause the construction to fail. Correct policy making is very important. Construction decision making used to depend on managerial staff’ experience and subjective recognition, but this approach is likely to bring about wrong decisions because of an excessive number of
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An Integration of Sentiment Analysis and MCDM Approach for Smartphone Recommendation Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-07-29 Gaurav Kumar; N. Parimala
Today, smartphones are being used to manage almost all aspects of our lives, ranging from personal to professional. Different users have different requirements and preferences while selecting a smartphone. There is ‘no one-size fits all’ remedy when it comes to smartphones. Additionally, the availability of a wide variety of smartphones in the market makes it difficult for the user to select the best
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Improving Human Performance in Dynamic Tasks with Debriefing-Based Interactive Learning Environments: An Empirical Investigation Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-07-23 Hassan Qudrat-Ullah
Dynamic tasks are pervasive in organizational decision making. Improving managerial performance in dynamic tasks is an ongoing research endeavor. We report a laboratory experiment in which participants managed a dynamic task by playing the roles of fishing fleet managers. The two experimental groups used a computer simulation-based interactive learning environment (ILE) with an outcome-oriented debriefing
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A Review on Some Arithmetic Concepts of Z-Number and Its Application to Real-World Problems Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-07-23 Mujahid Abdullahi; Tahir Ahmad; Vinod Ramachandran
Zadeh introduced the concept of Z-numbers in 2011 to deal with imprecise information. In this regard, many research works have been published in an attempt to introduce some basic theoretical concepts of Z-numbers to model real-world problems. To understand the current challenges when dealing with Z-numbers and the feasibility of using Z-number in solving real-world problems, a comprehensive review
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Fuzzy Numbers and Fractional Programming in Making Decisions Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-07-22 Bogdana Stanojević; Simona Dzitac; Ioan Dzitac
This study surveys the use of fuzzy numbers in classic optimization models, and its effects on making decisions. In a wide sense, mathematical programming is a collection of tools used in mathematical optimization to make good decisions. There are many sectors of economy that employ it. Finance and government, logistics and manufacturing, the distribution of the electrical power are worth to be first
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An Extension-Based Classification System of Cloud Computing Patents Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-07-20 Jia-Yen Huang; Ke-Wei Tan
Owing to the large number of professional glossaries and unknown patent classification, analysts usually fail to collect and analyze patents efficiently. One solution to this problem is to conduct patent analysis using a patent classification system. However, in a corpus such as cloud patents, many keywords are common among different classes, making it difficult to classify the unknown class documents
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Decision Support Research in Warehousing and Distribution: A Systematic Literature Review Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-06-12 Tania Binos; Arthur Adamopoulos; Vince Bruno
The increase in e-commerce and omnichannel commerce is having a significant impact on the supply chain sector and its warehouses. Fluctuations in demand and priorities, the requirement for value-added service, government regulations and other factors put pressure on the operational decision makers on the warehouse floor and the systems that support them. The increasing complexity of daily warehouse
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A New Index for TOPSIS based on Relative Distance to Best and Worst Points Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-06-11 S. A. Sadabadi; A. Hadi-Vencheh; A. Jamshidi; M. Jalali
The technique for order performance by similarity to ideal solution (TOPSIS) is one of the most well-known methods in multiple criteria decision making (MCDM) problems. The classical TOPSIS method employs a similarity index to rank alternatives. However, the chosen alternative sometimes does not have the shortest distance to the positive ideal solution (PIS) and remotest distance from the negative
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Multi-Scale Shapelets Discovery for Time-Series Classification Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-06-05 Borui Cai; Guangyan Huang; Yong Xiang; Maia Angelova; Limin Guo; Chi-Hung Chi
Shapelets are subsequences of time-series that represent local patterns and can improve the accuracy and the interpretability of time-series classification. The major task of time-series classification using shapelets is to discover high quality shapelets. However, this is challenging since local patterns may have various scales/lengths rather than a unified scale. In this paper, we resolve this problem
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Sustainable Location Selection of Data Centers: Developing a Multi-Criteria Set-Covering Decision-Making Methodology Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-06-24 Siamak Kheybari; Mansoor Davoodi Monfared; Hadis Farazmand; Jafar Rezaei
In this paper, a multi-criteria set-covering methodology is proposed to select suitable locations for a set of data centers. First, a framework of criteria, with social, economic and environmental dimensions, is presented. The framework is used to calculate the suitability of potential data center locations in Iran. To that end, a sample of specialists in Iran was asked to take part in an online questionnaire
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Novel Multiperspective Hiring Framework for the Selection of Software Programmer Applicants Based on AHP and Group TOPSIS Techniques Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-06-11 A. A. Zaidan; B. B. Zaidan; M. A. Alsalem; Fayiz Momani; Omar Zughoul
The selection of software programmer applicants based on multiperspective evaluation criteria (grade point average (GPA) and soft skills of the applicants) is needed instead of an interview because an interview does not necessarily lead to hiring the best candidate amongst the applicants. The selection of a suitable software programmer is considered a challenging task owing to the following factors:
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A Lightweight Approach to Extract Interschema Properties from Structured, Semi-Structured and Unstructured Sources in a Big Data Scenario Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-06-12 Francesco Cauteruccio; Paolo Lo Giudice; Lorenzo Musarella; Giorgio Terracina; Domenico Ursino; Luca Virgili
The knowledge of interschema properties (e.g., synonymies, homonymies, hyponymies and subschema similarities) plays a key role for allowing decision-making in sources characterized by disparate formats. In the past, wide amount and variety of approaches to derive interschema properties from structured and semi-structured data have been proposed. However, currently, it is esteemed that more than 80%
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A Concentration Ratio for Nonlinear Best Worst Method Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-06-11 Jafar Rezaei
Best Worst Method (BWM) is a multi-criteria decision-making method that is based on a structured pairwise comparison system. It uses two pairwise comparison vectors (best-to-others and others-to-worst) as input for an optimization model to get the optimal weights of the criteria (or alternatives). The original BWM involves a nonlinear model that sometimes results in multiple optimal weights meaning
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A Novel Multi-Perspective Benchmarking Framework for Selecting Image Dehazing Intelligent Algorithms Based on BWM and Group VIKOR Techniques Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-06-11 Karrar Hameed Abdulkareem; Nureize Arbaiy; A. A. Zaidan; B. B. Zaidan; O. S. Albahri; M. A. Alsalem; Mahmood M. Salih
The increasing demand for image dehazing-based applications has raised the value of efficient evaluation and benchmarking for image dehazing algorithms. Several perspectives, such as inhomogeneous foggy, homogenous foggy, and dark foggy scenes, have been considered in multi-criteria evaluation. The benchmarking for the selection of the best image dehazing intelligent algorithm based on multi-criteria
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Integrating Sentiment Analysis on Hybrid Collaborative Filtering Method in a Big Data Environment Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-05-04 P. Shanmuga Sundari; M. Subaji
Most of the traditional recommendation systems are based on user ratings. Here, users provide the ratings towards the product after use or experiencing it. Accordingly, the user item transactional database is constructed for recommendation. The rating based collaborative filtering method is well known method for recommendation system. This system leads to data sparsity problem as the user is unaware
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Pre-Evaluating the Technical Efficiency Gains from Potential Mergers and Acquisitions in the IC Design Industry Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-04-30 Ying Li; Yung-Ho Chiu; Tai-Yu Lin; Tzu-Han Chang
Increased global competition has led to a slowdown in Taiwan’s domestic semiconductor industry growth, which has resulted in many semiconductor companies reducing their investments and or seeking mergers and acquisitions (M & As) to increase market power, expand their business territories or increase their competitive edge. However, as there is general uncertainty regarding the efficiencies to be gained
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A Multi-Attribute Group Decision-Making Method Based on Linguistic Intuitionistic Fuzzy Numbers and Dempster–Shafer Evidence Theory Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-04-21 Peide Liu; Xiaoxiao Liu; Guiying Ma; Zhaolong Liang; Changhai Wang; Fawaz E. Alsaadi
In this paper, we propose a multi-attribute group decision-making (MAGDM) method based on Dempster–Shafer Evidence Theory (DST) and linguistic intuitionistic fuzzy numbers (LIFNs), in which both the expert weights and attribute weights are unknown. Firstly, we represent LIFNs as basic probability assignments (BPAs) by DST based on linguistic scale function (LSF), and a linear programming model is proposed
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Using Ordered Weighted Average for Weighted Averages Inflation Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-04-21 Luis F. Espinoza-Audelo; Ernesto León-Castro; Marycruz Olazabal-Lugo; José M. Merigó; Anna M. Gil-Lafuente
This paper presents the ordered weighted average weighted average inflation (OWAWAI) and some extensions using induced and heavy aggregation operators and presents the generalized operators and some of their families. The main advantage of these new formulations is that they can use two different sets of weighting vectors and generate new scenarios based on the reordering of the arguments with the
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An Artificial Bee Colony-Guided Approach for Electro-Encephalography Signal Decomposition-Based Big Data Optimization Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-04-20 Selcuk Aslan
The digital age has added a new term to the literature of information and computer sciences called as the big data in recent years. Because of the individual properties of the newly introduced term, the definitions of the data-intensive problems including optimization problems have been substantially changed and investigations about the solving capabilities of the existing techniques and then developing
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A Novel Hybrid Fuzzy AHP-GA Method for Test Sheet Question Selection Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-04-17 Murat İnce; Tuncay Yiğit; Ali Hakan Işik
The use of web-based education and e-learning environments has increased with the developments in educational technology. Schools, universities, public institutions, and other private sector companies started deploying these systems to train their students, members, and employees. Exams are carried out during the evaluation process of these trainings. Web-based tests are sometimes used for these exams
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Cloud Computing-Based Socially Important Locations Discovery on Social Media Big Datasets Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-03-25 Ahmet Sakir Dokuz; Mete Celik
Socially important locations are places which are frequently visited by social media users in their social media lifetime. Discovering socially important locations provides valuable information, such as which locations are frequently visited by a social media user, which locations are common for a social media user group, and which locations are socially important for a group of urban area residents
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A Modified Balanced Scorecard Based Hybrid Pythagorean Fuzzy AHP-Topsis Methodology for ATM Site Selection Problem Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-03-20 Aslihan Yildiz; Ertugrul Ayyildiz; Alev Taskin Gumus; Coskun Ozkan
Researchers work on facility location problems in different structures and solve them by developing different models over the years. In this study, we focus on the automated teller machine (ATM) site selection problem for a public bank in İstanbul. Twenty-five districts, which are located at the European side of İstanbul, are designated as ATM candidate districts. The balanced scorecard (BSC) model
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A DSS-Based Novel Approach Proposition Employing Decision Techniques for System Design Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-03-10 Burcu Yılmaz Kaya; Aylin Adem; Metin Dağdeviren
In this study, to enhance flexibility and agility, a special DSS is developed for a system re-design problem, while a decision-making technique is employed afterwards to enable the accelerated and reliable results, as a progressive approach to close a gap of related literature. Proposed approach generates all possible machine schedules regarding some tangible traditional constraints, after that, generated
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Effect of Social Media Interactions on CLV in Telecommunications Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-03-10 Oğuzhan Kivrak; Cüneyt Akar
The main goal of this study is to investigate whether social media, as a recent communication channel, has an impact on customer lifetime value (CLV). No studies have been done in Turkey with similar purposes in the telecommunication sector. To reach this goal, there has been an attempt to develop both artificial neural network models and sector-specific applicable models. Four years of data between
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Subset Selection Using Frequency Decomposition with Applications Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-03-05 W. M. Tang; K. F. C. Yiu; H. Wong
In time series modeling, one problem is to identify a small number of influential factors to explain variations in the variable of interest. With a vast number of possible factors available, suitable features need to be identified to yield multi-factor models with good explanatory power. In this paper, we propose a novel subset selection method which makes use of the properties in the frequency domain
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A Novel Flash P2P Network Traffic Prediction Algorithm based on ELMD and Garch Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-03-03 Yimu Ji; Ye Wu; Dianchao Zhang; Yongge Yuan; Shangdong Liu; Roozbeh Zarei; Jing He
To improve the quality of service and network performance for the Flash P2P video-on-demand, the prediction Flash P2P network traffic flow is beneficial for the control of the network video traffic. In this paper, a novel prediction algorithm to forecast the traffic rate of Flash P2P video is proposed. This algorithm is based on the combination of the ensemble local mean decomposition (ELMD) and the
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A Correlation-Based TOPSIS Method for Multiple Attribute Decision Making with Single-Valued Neutrosophic Information Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-02-25 Shouzhen Zeng; Dandan Luo; Chonghui Zhang; Xingsen Li
The single-valued neutrosophic set (SVNS) is considered as an attractive tool for handling highly uncertain and vague information. With this regard, different from the most current distance-based technique for order preference by similarity to ideal solution (TOPSIS) methods, this study proposes a correlation-based TOPSIS model for addressing the single-valued neutrosophic (SVN) multiple attribute
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A Review on Human-Computer Interaction and Intelligent Robots Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-02-17 Fuji Ren; Yanwei Bao
In the field of artificial intelligence, human–computer interaction (HCI) technology and its related intelligent robot technologies are essential and interesting contents of research. From the perspective of software algorithm and hardware system, these above-mentioned technologies study and try to build a natural HCI environment. The purpose of this research is to provide an overview of HCI and intelligent
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Clustering Categorical Data: A Survey Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-02-04 Sami Naouali; Semeh Ben Salem; Zied Chtourou
Clustering is a complex unsupervised method used to group most similar observations of a given dataset within the same cluster. To guarantee high efficiency, the clustering process should ensure high accuracy and low complexity. Many clustering methods were developed in various fields depending on the type of application and the data type considered. Categorical clustering considers segmenting a dataset
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Adapted Visual Analytics Process for Intelligent Decision-Making: Application in a Medical Context Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-02-03 Hela Ltifi; Emna Benmohamed; Christophe Kolski; Mounir Ben Ayed
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
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Dependence Structure Analysis and VaR Estimation Based on China’s and International Gold Price: A Copula Approach Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-02-03 Zhicheng Liang; Junwei Wang; Kin Keung Lai
Since 2013, China has become the world’s largest gold producer and consumer. To gain the corresponding global pricing power in gold, many actions have been taken by China in recent years, including the International Board at Shanghai Gold Exchange, Shanghai-Hong Kong Gold Connect and Shanghai Gold Fix. Our work studies the dependence structure between China’s and international gold price and examines
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LAMDA-HAD, an Extension to the LAMDA Classifier in the Context of Supervised Learning Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-01-31 Luis Morales; José Aguilar; Danilo Chávez; Claudia Isaza
This paper proposes a new approach to improve the performance of Learning Algorithm for Multivariable Data Analysis (LAMDA). This algorithm can be used for supervised and unsupervised learning, based on the calculation of the Global Adequacy Degree (GAD) of one individual to a class, through the contributions of all its descriptors. LAMDA has the capability of creating new classes after the training
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A Research Review and Taxonomy Development for Decision Support and Business Analytics Using Semantic Text Mining Int. J. Inf. Technol. Decis. Mak. (IF 1.894) Pub Date : 2020-01-28 Andrea Ko; Saira Gillani
By 2018, business analytics (BA), believed by global CIOs to be of strategic importance, had for years been their top priority. It is also a focus of academic research, as shown by a large number of papers, books, and research reports. On the other hand, the BA domain suffers from several incorrect, imprecise, and incomplete notions. New areas and concepts emerge quickly; making it difficult to ascertain