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  • Open Access

    ARTICLE

    Frequent Itemset Mining of User’s Multi-Attribute under Local Differential Privacy

    Haijiang Liu1, Lianwei Cui2, Xuebin Ma1, *, Celimuge Wu3

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 369-385, 2020, DOI:10.32604/cmc.2020.010987

    Abstract Frequent itemset mining is an essential problem in data mining and plays a key role in many data mining applications. However, users’ personal privacy will be leaked in the mining process. In recent years, application of local differential privacy protection models to mine frequent itemsets is a relatively reliable and secure protection method. Local differential privacy means that users first perturb the original data and then send these data to the aggregator, preventing the aggregator from revealing the user’s private information. We propose a novel framework that implements frequent itemset mining under local differential privacy and is applicable to user’s… More >

  • Open Access

    ARTICLE

    An Opinion Spam Detection Method Based on Multi-Filters Convolutional Neural Network

    Ye Wang1, Bixin Liu2, Hongjia Wu1, Shan Zhao1, Zhiping Cai1, *, Donghui Li3, *, Cheang Chak Fong4

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 355-367, 2020, DOI:10.32604/cmc.2020.09835

    Abstract With the continuous development of e-commerce, consumers show increasing interest in posting comments on consumption experience and quality of commodities. Meanwhile, people make purchasing decisions relying on other comments much more than ever before. So the reliability of commodity comments has a significant impact on ensuring consumers’ equity and building a fair internet-trade-environment. However, some unscrupulous online-sellers write fake praiseful reviews for themselves and malicious comments for their business counterparts to maximize their profits. Those improper ways of self-profiting have severely ruined the entire online shopping industry. Aiming to detect and prevent these deceptive comments effectively, we construct a model… More >

  • Open Access

    ARTICLE

    An Improved Algorithm for Mining Correlation Item Pairs

    Tao Li1, Yongzhen Ren1, *, Yongjun Ren2, Jinyue Xia3

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 337-354, 2020, DOI:10.32604/cmc.2020.06462

    Abstract Apriori algorithm is often used in traditional association rules mining, searching for the mode of higher frequency. Then the correlation rules are obtained by detected the correlation of the item sets, but this tends to ignore low-support high-correlation of association rules. In view of the above problems, some scholars put forward the positive correlation coefficient based on Phi correlation to avoid the embarrassment caused by Apriori algorithm. It can dig item sets with low-support but high-correlation. Although the algorithm has pruned the search space, it is not obvious that the performance of the running time based on the big data… More >

  • Open Access

    ARTICLE

    A Cache Replacement Policy Based on Multi-Factors for Named Data Networking

    Meiju Yu1, Ru Li1, *, Yuwen Chen2

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 321-336, 2020, DOI:10.32604/cmc.2020.010831

    Abstract Named Data Networking (NDN) is one of the most excellent future Internet architectures and every router in NDN has the capacity of caching contents passing by. It greatly reduces network traffic and improves the speed of content distribution and retrieval. In order to make full use of the limited caching space in routers, it is an urgent challenge to make an efficient cache replacement policy. However, the existing cache replacement policies only consider very few factors that affect the cache performance. In this paper, we present a cache replacement policy based on multi-factors for NDN (CRPM), in which the content… More >

  • Open Access

    ARTICLE

    Applying Stack Bidirectional LSTM Model to Intrusion Detection

    Ziyong Ran1, Desheng Zheng1, *, Yanling Lai1, Lulu Tian2

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 309-320, 2020, DOI:10.32604/cmc.2020.010102

    Abstract Nowadays, Internet has become an indispensable part of daily life and is used in many fields. Due to the large amount of Internet traffic, computers are subject to various security threats, which may cause serious economic losses and even endanger national security. It is hoped that an effective security method can systematically classify intrusion data in order to avoid leakage of important data or misuse of data. As machine learning technology matures, deep learning is widely used in various industries. Combining deep learning with network security and intrusion detection is the current trend. In this paper, the problem of data… More >

  • Open Access

    ARTICLE

    Software Defect Prediction Based on Stacked Contractive Autoencoder and Multi-Objective Optimization

    Nana Zhang1, Kun Zhu1, Shi Ying1, *, Xu Wang2

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 279-308, 2020, DOI:10.32604/cmc.2020.011001

    Abstract Software defect prediction plays an important role in software quality assurance. However, the performance of the prediction model is susceptible to the irrelevant and redundant features. In addition, previous studies mostly regard software defect prediction as a single objective optimization problem, and multi-objective software defect prediction has not been thoroughly investigated. For the above two reasons, we propose the following solutions in this paper: (1) we leverage an advanced deep neural network—Stacked Contractive AutoEncoder (SCAE) to extract the robust deep semantic features from the original defect features, which has stronger discrimination capacity for different classes (defective or non-defective). (2) we… More >

  • Open Access

    ARTICLE

    A Structure Preserving Numerical Method for Solution of Stochastic Epidemic Model of Smoking Dynamics

    Ali Raza1, Muhammad Rafiq2, Nauman Ahmed3, Ilyas Khan4, *, Kottakkaran Sooppy Nisar5, Zafar Iqbal3

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 263-278, 2020, DOI:10.32604/cmc.2020.011289

    Abstract In this manuscript, we consider a stochastic smoking epidemic model from behavioural sciences. Also, we develop a structure preserving numerical method to describe the dynamics of stochastic smoking epidemic model in a human population. The structural properties of a physical system include positivity, boundedness and dynamical consistency. These properties play a vital role in non-linear dynamics. The solution for nonlinear stochastic models necessitates the conservation of these properties. Unfortunately, the aforementioned properties of the model have not been restored in the existing stochastic methods. Therefore, it is essential to construct a structure preserving numerical method for a reliable analysis of… More >

  • Open Access

    ARTICLE

    Network-Aided Intelligent Traffic Steering in 5G Mobile Networks

    Dae-Young Kim1, Seokhoon Kim2, *

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 243-261, 2020, DOI:10.32604/cmc.2020.011253

    Abstract Recently, the fifth generation (5G) of mobile networks has been deployed and various ranges of mobile services have been provided. The 5G mobile network supports improved mobile broadband, ultra-low latency and densely deployed massive devices. It allows multiple radio access technologies and interworks them for services. 5G mobile systems employ traffic steering techniques to efficiently use multiple radio access technologies. However, conventional traffic steering techniques do not consider dynamic network conditions efficiently. In this paper, we propose a network aided traffic steering technique in 5G mobile network architecture. 5G mobile systems monitor network conditions and learn with network data. Through… More >

  • Open Access

    ARTICLE

    Dynamical Behavior and Sensitivity Analysis of a Delayed Coronavirus Epidemic Model

    Muhammad Naveed1, *, Dumitru Baleanu2, 3, 4, Muhammad Rafiq5, Ali Raza6, Atif Hassan Soori1, Nauman Ahmed7

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 225-241, 2020, DOI:10.32604/cmc.2020.011534

    Abstract Mathematical delay modelling has a significant role in the different disciplines such as behavioural, social, physical, biological engineering, and bio-mathematical sciences. The present work describes mathematical formulation for the transmission mechanism of a novel coronavirus (COVID-19). Due to the unavailability of vaccines for the coronavirus worldwide, delay factors such as social distance, quarantine, travel restrictions, extended holidays, hospitalization, and isolation have contributed to controlling the coronavirus epidemic. We have analysed the reproduction number and its sensitivity to parameters. If, More >

  • Open Access

    ARTICLE

    Simulation of Water-Soil-Structure Interactions Using Incompressible Smoothed Particle Hydrodynamics

    Abdelraheem M. Aly1, 2, *, Mitsuteru Asai3, Ehab Mahmoud Mohamed4, 5

    CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 205-224, 2020, DOI:10.32604/cmc.2020.09227

    Abstract In the present work, an incompressible smoothed particle hydrodynamic (SPH) method is introduced to simulate water-soil-structure interactions. In the current calculation, the water is modelled as a Newtonian fluid. The soil is modelled in two different cases. In the first case, the granular material is considered as a fluid where a Bingham type constitutive model is proposed based on Mohr-Coulomb yield-stress criterion, and the viscosity is derived from the cohesion and friction angle. In addition, the fictitious suspension layers between water and soil depending on the concentration of soil are introduced. In the second case, Hooke’s law introduces elastic soil.… More >

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