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Who is the boss? Identifying key roles in telecom fraud network via centrality-guided deep random walk Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-04 Yi-Chun Chang; Kuan-Ting Lai; Seng-Cho T. Chou; Wei-Chuan Chiang; Yuan-Chen Lin
Purpose Telecommunication (telecom) fraud is one of the most common crimes and causes the greatest financial losses. To effectively eradicate fraud groups, the key fraudsters must be identified and captured. One strategy is to analyze the fraud interaction network using social network analysis. However, the underlying structures of fraud networks are different from those of common social networks,
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Enhancing lifetime of wireless multimedia sensor networks using modified lion algorithm–based image transmission model Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-06 Mahesh P. Wankhade; KC Jondhale
Purpose In the past few decades, the wireless sensor network (WSN) has become the more vital one with the involvement of the conventional WSNs and wireless multimedia sensor networks (WMSNs). The network that is composed of low-power, small-size, low-cost sensors is said to be WSN. Here, the communication information is handled using the multiple hop and offers only a simple sensing data, such as humidity
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An error-propagation aware method to reduce the software mutation cost using genetic algorithm Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-12 Seyed Mohammad Javad Hosseini; Bahman Arasteh; Ayaz Isazadeh; Mehran Mohsenzadeh; Mitra Mirzarezaee
Purpose The purpose of this study is to reduce the number of mutations and, consequently, reduce the cost of mutation test. The results of related studies indicate that about 40% of injected faults (mutants) in the source code are effect-less (equivalent). Equivalent mutants are one of the major costs of mutation testing and the identification of equivalent and effect-less mutants has been known as
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An effective recommender system based on personality traits, demographics and behavior of customers in time context Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-10 Samira Khodabandehlou; S. Alireza Hashemi Golpayegani; Mahmoud Zivari Rahman
Purpose Improving the performance of recommender systems (RSs) has always been a major challenge in the area of e-commerce because the systems face issues such as cold start, sparsity, scalability and interest drift that affect their performance. Despite the efforts made to solve these problems, there is still no RS that can solve or reduce all the problems simultaneously. Therefore, the purpose of
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Population estimation using Twitter for a specific space Data Technol. Appl. (IF 0.704) Pub Date : 2021-01-13 Hiroki Hara; Yoshikatsu Fujita; Kazuhiko Tsuda
Purpose This paper aims to estimate the population in a specific space from the numbers of posted tweets and their senders, using Twitter's real-time property and location information data. Design/methodology/approach The population to be estimated was set to be the attendance at each game among the six baseball teams of the Japan Professional Baseball Pacific League held at the main stadium of each
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Assessment of national innovation capabilities of OECD countries using trapezoidal interval type-2 fuzzy ELECTRE III method Data Technol. Appl. (IF 0.704) Pub Date : 2020-12-31 Geetha Selvaraj; Jeonghwan Jeon
Purpose For a nation to become a superpower, it's scientific and technological advancement is essential. Each country is exploring how to improve themselves in terms of science and technology. The authors analyzed the innovation capabilities of 35 OECD countries that have not recently joined Lithuania. Design/methodology/approach In recent years, a lot of research work has been done on trapezoidal
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Structural equation modeling and artificial neural networks approach to predict continued use of mobile taxi booking apps: the mediating role of hedonic motivation Data Technol. Appl. (IF 0.704) Pub Date : 2020-12-15 Abdul Waheed Siyal; Hongzhuan Chen; Gang Chen; Muhammad Mujahid Memon; Zainab Binte
Purpose Mobile taxi booking apps (MTB) have revolutionalized the transportation industry. As taxis can be hired via smartphones, irrespective of any time or place, the business platform for taxi service has completely changed. Now customers are saved from the hassle of going to the designated taxi stands or waiting along the roadside. But, the long-term sustainability of this service depends on its
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Measuring semantic distances using linked open data and its application on music recommender systems Data Technol. Appl. (IF 0.704) Pub Date : 2020-12-08 Hsin-Chang Yang; Chung-Hong Lee; Wen-Sheng Liao
Purpose Measuring the similarity between two resources is considered difficult due to a lack of reliable information and a wide variety of available information regarding the resources. Many approaches have been devised to tackle such difficulty. Although content-based approaches, which adopted resource-related data in comparing resources, played a major role in similarity measurement methodology,
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Bölen: software module clustering method using the combination of shuffled frog leaping and genetic algorithm Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-27 Bahman Arasteh; Razieh Sadegi; Keyvan Arasteh
Purpose Software module clustering is one of the reverse engineering techniques, which is considered to be an effective technique for presenting software architecture and structural information. The objective of clustering software modules is to achieve minimum coupling among different clusters and create maximum cohesion among the modules of each cluster. Finding the best clustering is considered
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An efficient local search for large-scale set-union knapsack problem Data Technol. Appl. (IF 0.704) Pub Date : 2020-12-01 Yupeng Zhou; Mengyu Zhao; Mingjie Fan; Yiyuan Wang; Jianan Wang
Purpose The set-union knapsack problem is one of the most significant generalizations of the Non-deterministic Polynomial (NP)-hard 0-1 knapsack problem in combinatorial optimization, which has rich application scenarios. Although some researchers performed effective algorithms on normal-sized instances, the authors found these methods deteriorated rapidly as the scale became larger. Therefore, the
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Using photographs and metadata to estimate house prices in South Korea Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-24 Changro Lee; Key-Ho Park
Purpose Most prior attempts at real estate valuation have focused on the use of metadata such as size and property age, neglecting the fact that the building workmanship in the construction of a house is also a key factor for the estimation of house prices. Building workmanship, such as exterior walls and floor tiling correspond to the visual attributes of a house, and it is difficult to capture and
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Data access as a big competitive advantage: evidence from China's car-hailing platforms Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-17 Lei Huang; Yandong Zhao; Guangxi He; Yangxu Lu; Juanjuan Zhang; Peiyi Wu
Purpose The online platform is one of the essential components of the platform economy that is constructed by a large scale of the personal data resource. However, accurate empirical test of the competition structure of the data-driven online platform is still less. This research is trying to reveal market allocation structure of the personal data resource of China's car-hailing platforms competition
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Gradient boosting learning for fraudulent publisher detection in online advertising Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-17 Deepti Sisodia; Dilip Singh Sisodia
Purpose Analysis of the publisher's behavior plays a vital role in identifying fraudulent publishers in the pay-per-click model of online advertising. However, the vast amount of raw user click data with missing values pose a challenge in analyzing the conduct of publishers. The presence of high cardinality in categorical attributes with multiple possible values has further aggrieved the issue. De
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Optimal support vector machine and hybrid tracking model for behaviour recognition in highly dense crowd videos Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-03 K. Satya Sujith; G. Sasikala
Purpose Object detection models have gained considerable popularity as they aid in lot of applications, like monitoring, video surveillance, etc. Object detection through the video tracking faces lot of challenges, as most of the videos obtained as the real time stream are affected due to the environmental factors. Design/methodology/approach This research develops a system for crowd tracking and crowd
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A novel dual-domain clustering algorithm for inhomogeneous spatial point event Data Technol. Appl. (IF 0.704) Pub Date : 2020-10-28 Jie Zhu; Jing Yang; Shaoning Di; Jiazhu Zheng; Leying Zhang
Purpose The spatial and non-spatial attributes are the two important characteristics of a spatial point, which belong to the two different attribute domains in many Geographic Information Systems applications. The dual clustering algorithms take into account both spatial and non-spatial attributes, where a cluster has not only high proximity in spatial domain but also high similarity in non-spatial
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Data science and its relationship to library and information science: a content analysis Data Technol. Appl. (IF 0.704) Pub Date : 2020-10-13 Sirje Virkus; Emmanouel Garoufallou
Purpose The purpose of this paper is to present the results of a study exploring the emerging field of data science from the library and information science (LIS) perspective. Design/methodology/approach Content analysis of research publications on data science was made of papers published in the Web of Science database to identify the main themes discussed in the publications from the LIS perspective
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Electrocardiogram stream level correlated patterns as features to classify heartbeats for arrhythmia prediction Data Technol. Appl. (IF 0.704) Pub Date : 2020-10-26 Fuad Ali Mohammed Al-Yarimi; Nabil Mohammed Ali Munassar; Fahd N. Al-Wesabi
Purpose Digital computing and machine learning-driven predictive analysis in the diagnosis of non-communicable diseases are gaining significance. Globally many research studies are focusing on developing comprehensive models for such detection. Categorically in the proposed diagnosis for arrhythmia, which is a critical diagnosis to prevent cardiac-related deaths, any constructive models can be a value
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Sequel movie revenue prediction model based on sentiment analysis Data Technol. Appl. (IF 0.704) Pub Date : 2020-10-08 Ibrahim Said Ahmad; Azuraliza Abu Bakar; Mohd Ridzwan Yaakub; Mohammad Darwich
Purpose Sequel movies are very popular; however, there are limited studies on sequel movie revenue prediction. The purpose of this paper is to propose a sentiment analysis based model for sequel movie revenue prediction and to propose a missing value imputation method for the sequel revenue prediction dataset. Design/methodology/approach A sequel of a successful movie will most likely also be successful
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Embedding based learning for collection selection in federated search Data Technol. Appl. (IF 0.704) Pub Date : 2020-10-28 Adamu Garba; Shah Khalid; Irfan Ullah; Shah Khusro; Diyawu Mumin
Purpose There have been many challenges in crawling deep web by search engines due to their proprietary nature or dynamic content. Distributed Information Retrieval (DIR) tries to solve these problems by providing a unified searchable interface to these databases. Since a DIR must search across many databases, selecting a specific database to search against the user query is challenging. The challenge
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Technical trends of artificial intelligence in standard-essential patents Data Technol. Appl. (IF 0.704) Pub Date : 2020-11-02 Shu-Hao Chang
Purpose Defining key artificial intelligence (AI) technologies is especially fundamental because AI applications involve the development of multiple technical fields and have the potential to generate numerous business opportunities in the future. However, most related studies have examined patent grants granted by or patent applications filed to major patent offices; few studies have employed the
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TrCSVM: a novel approach for the classification of melanoma skin cancer using transfer learning Data Technol. Appl. (IF 0.704) Pub Date : 2020-10-27 Lokesh Singh; Rekh Ram Janghel; Satya Prakash Sahu
Purpose The study aims to cope with the problems confronted in the skin lesion datasets with less training data toward the classification of melanoma. The vital, challenging issue is the insufficiency of training data that occurred while classifying the lesions as melanoma and non-melanoma. Design/methodology/approach In this work, a transfer learning (TL) framework Transfer Constituent Support Vector
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An algorithm to elicitate ELECTRE II, III and IV parameters Data Technol. Appl. (IF 0.704) Pub Date : 2020-10-23 Brunno e Souza Rodrigues; Carla Martins Floriano; Valdecy Pereira; Marcos Costa Roboredo
Purpose This paper presents an algorithm that can elicitate all or any combination of parameters for the ELECTRE II, III or IV, methods. The algorithm takes some steps of a machine learning ensemble technique, the random forest, and for that, the authors named the approach as Ranking Trees Algorithm. Design/methodology/approach First, for a given method, the authors generate a set of ELECTRE models
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Entity deduplication in big data graphs for scholarly communication Data Technol. Appl. (IF 0.704) Pub Date : 2020-06-26 Paolo Manghi; Claudio Atzori; Michele De Bonis; Alessia Bardi
Purpose Several online services offer functionalities to access information from “big research graphs” (e.g. Google Scholar, OpenAIRE, Microsoft Academic Graph), which correlate scholarly/scientific communication entities such as publications, authors, datasets, organizations, projects, funders, etc. Depending on the target users, access can vary from search and browse content to the consumption of
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Enhancement of low voltage ride-through ability of the photovoltaic array aided by the MPPT algorithm connected with wind turbine Data Technol. Appl. (IF 0.704) Pub Date : 2020-06-30 Charanjeet Madan; Naresh Kumar
Purpose By means of the massive environmental and financial reimbursements, wind turbine (WT) has turned out to be a satisfactory substitute for the production of electricity by nuclear or fossil power plants. Numerous research studies are nowadays concerning the scheme to develop the performance of the WT into a doubly fed induction generator-low voltage ride-through (DFIG-LVRT) system, with utmost
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An optimization-based deep belief network for the detection of phishing e-mails Data Technol. Appl. (IF 0.704) Pub Date : 2020-07-16 Arshey M.; Angel Viji K. S.
Purpose Phishing is a serious cybersecurity problem, which is widely available through multimedia, such as e-mail and Short Messaging Service (SMS) to collect the personal information of the individual. However, the rapid growth of the unsolicited and unwanted information needs to be addressed, raising the necessity of the technology to develop any effective anti-phishing methods. Design/methodology/approach
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Integrated data envelopment analysis and multicriteria decision-making ranking approach based on peer-evaluations and subjective preferences: case study in banking sector Data Technol. Appl. (IF 0.704) Pub Date : 2020-07-12 Jolly Puri; Meenu Verma
Purpose This paper is focused on developing an integrated algorithmic approach named as data envelopment analysis and multicriteria decision-making (DEA-MCDM) for ranking decision-making units (DMUs) based on cross-efficiency technique and subjective preference(s) of the decision maker. Design/methodology/approach Self-evaluation in data envelopment analysis (DEA) lacks in discrimination power among
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Investigating the repurchase intention of Bitcoin: empirical evidence from China Data Technol. Appl. (IF 0.704) Pub Date : 2020-08-07 Muhammad Athar Nadeem; Zhiying Liu; Abdul Hameed Pitafi; Amna Younis; Yi Xu
Purpose Cryptocurrencies, such as Bitcoin, generate innovative and fast exchanges without any physical form and facilitate online payments; thus, they may bring about revolutions of the future economic system. Recent investigations reveal that China, the second largest Bitcoin market, accounts for a huge volume of Bitcoin trading and mining, which can cast distinct influences on future values of Bitcoin
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Evolution of conformal antenna design with the aid of probability improved crow search algorithm Data Technol. Appl. (IF 0.704) Pub Date : 2020-07-31 Nama Ajay Nagendra; Lakshman Pappula
Purpose The issues of radiating sources in the existence of smooth convex matters by such objects are of huge significance in the modeling of antennas on structures. Conformal antenna arrays are necessary when an antenna has to match to certain platforms. A fundamental problem in the design is that the possible surfaces for a conformal antenna are infinite in number. Furthermore, if there is no symmetry
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Chicken swarm foraging algorithm for big data classification using the deep belief network classifier Data Technol. Appl. (IF 0.704) Pub Date : 2020-07-29 Sathyaraj R; Ramanathan L; Lavanya K; Balasubramanian V; Saira Banu J
Purpose The innovation in big data is increasing day by day in such a way that the conventional software tools face several problems in managing the big data. Moreover, the occurrence of the imbalance data in the massive data sets is a major constraint to the research industry. Design/methodology/approach The purpose of the paper is to introduce a big data classification technique using the MapReduce
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The relative decision-making algorithm for ranking data Data Technol. Appl. (IF 0.704) Pub Date : 2020-06-30 Yin-Ju Chen; Jian-Ming Lo
Purpose Decision-making is always an issue that managers have to deal with. Keenly observing to different preferences of the targets provides useful information for decision-makers who do not require too much information to make decisions. The main purpose is to avoid decision-makers in a dilemma because of too much or opaque information. Based on problem-oriented, this research aims to help decision-makers
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Distributed elephant herding optimization for grid-based privacy association rule mining Data Technol. Appl. (IF 0.704) Pub Date : 2020-05-15 Praveen Kumar Gopagoni; Mohan Rao S K
Purpose Association rule mining generates the patterns and correlations from the database, which requires large scanning time, and the cost of computation associated with the generation of the rules is quite high. On the other hand, the candidate rules generated using the traditional association rules mining face a huge challenge in terms of time and space, and the process is lengthy. In order to tackle
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Recognizing ragas of Carnatic genre using advanced intelligence: a classification system for Indian music Data Technol. Appl. (IF 0.704) Pub Date : 2020-05-16 Balachandra Kumaraswamy; Poonacha P G
Purpose In general, Indian Classical Music (ICM) is classified into two: Carnatic and Hindustani. Even though, both the music formats have a similar foundation, the way of presentation is varied in many manners. The fundamental components of ICM are raga and taala. Taala basically represents the rhythmic patterns or beats (Dandawate et al., 2015; Kirthika and Chattamvelli, 2012). Raga is determined
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Incremental learning for text categorization using rough set boundary based optimized Support Vector Neural Network Data Technol. Appl. (IF 0.704) Pub Date : 2020-07-03 N. Venkata Sailaja; L. Padmasree; N. Mangathayaru
Purpose Text mining has been used for various knowledge discovery based applications, and thus, a lot of research has been contributed towards it. Latest trending research in the text mining is adopting the incremental learning data, as it is economical while dealing with large volume of information. Design/methodology/approach The primary intention of this research is to design and develop a technique
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Gift giving via social network services: the case of a WeChat mini-program used in China Data Technol. Appl. (IF 0.704) Pub Date : 2020-06-11 Chen Hao; Chen Hai-tao
Purpose The purpose of this paper is to examine and explore the factors that drive users to gift through social network services (SNS). Design/methodology/approach A questionnaire method was applied to collect data from the sample of the WeChat users who have used mini-program. This paper employed the partial least squares method and used SmartPLS2.0 to analysis sample data, which examined the validity
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Explanatory Q&A recommendation algorithm in community question answering Data Technol. Appl. (IF 0.704) Pub Date : 2020-06-05 Ming Li; Ying Li; YingCheng Xu; Li Wang
Purpose In community question answering (CQA), people who answer questions assume readers have mastered the content in the answers. Nevertheless, some readers cannot understand all content. Thus, there is a need for further explanation of the concepts that appear in the answers. Moreover, the large number of question and answer (Q&A) documents make manual retrieval difficult. This paper aims to alleviate
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Mutation reduction in software mutation testing using firefly optimization algorithm Data Technol. Appl. (IF 0.704) Pub Date : 2020-05-25 Nasrin Shomali; Bahman Arasteh
Purpose For delivering high-quality software applications, proper testing is required. A software test will function successfully if it can find more software faults. The traditional method of assessing the quality and effectiveness of a test suite is mutation testing. One of the main drawbacks of mutation testing is its computational cost. The research problem of this study is the high computational
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Characterization of path loss model for wireless communication channel modelling Data Technol. Appl. (IF 0.704) Pub Date : 2020-04-27 Nandakishor Sirdeshpande; Vishwanath Udupi
Purpose Wireless communication channel provides a wide area of applications in the field of communication, distributed sensor network and so on. The prominence of the wireless communication channel is because of its robust nature and the sustainability for the precise ranging and the localization. The precision and accuracy of the wireless communication channel largely depend on the localization. The
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LFOPI controller: a fractional order PI controller based load frequency control in two area multi-source interconnected power system Data Technol. Appl. (IF 0.704) Pub Date : 2020-04-25 Deepesh Sharma; Naresh Kumar Yadav
Purpose In computer application scenario, data mining task is rarely utilized in power system, as an enhanced part, this work presented data mining task in power systems, to overcome frequency deviation issues. Load frequency control (LFC) is a primary challenging problem in an interconnected multi-area power system. Design/methodology/approach This paper adopts lion algorithm (LA) for the LFC of two
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A novel speech emotion recognition model using mean update of particle swarm and whale optimization-based deep belief network Data Technol. Appl. (IF 0.704) Pub Date : 2020-04-16 Rajasekhar B; Kamaraju M; Sumalatha V
Purpose Nowadays, the speech emotion recognition (SER) model has enhanced as the main research topic in various fields including human–computer interaction as well as speech processing. Generally, it focuses on utilizing the models of machine learning for predicting the exact emotional status from speech. The advanced SER applications go successful in affective computing and human–computer interaction
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Global search in single-solution-based metaheuristics Data Technol. Appl. (IF 0.704) Pub Date : 2020-03-12 Najmeh Sadat Jaddi; Salwani Abdullah
Purpose Metaheuristic algorithms are classified into two categories namely: single-solution and population-based algorithms. Single-solution algorithms perform local search process by employing a single candidate solution trying to improve this solution in its neighborhood. In contrast, population-based algorithms guide the search process by maintaining multiple solutions located in different points
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A regression-based algorithm for frequent itemsets mining Data Technol. Appl. (IF 0.704) Pub Date : 2019-09-05 Zirui Jia; Zengli Wang
Purpose Frequent itemset mining (FIM) is a basic topic in data mining. Most FIM methods build itemset database containing all possible itemsets, and use predefined thresholds to determine whether an itemset is frequent. However, the algorithm has some deficiencies. It is more fit for discrete data rather than ordinal/continuous data, which may result in computational redundancy, and some of the results
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Performance analysis: Differential search algorithm based on randomization and benchmark functions Data Technol. Appl. (IF 0.704) Pub Date : 2019-07-16 Areej Ahmad Alsaadi; Wadee Alhalabi; Elena-Niculina Dragoi
Purpose Differential search algorithm (DSA) is a new optimization, meta-heuristic algorithm. It simulates the Brownian-like, random-walk movement of an organism by migrating to a better position. The purpose of this paper is to analyze the performance analysis of DSA into two key parts: six random number generators (RNGs) and Benchmark functions (BMF) from IEEE World Congress on Evolutionary Computation
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