Yulan Zheng^∗

Computer Systems Science and Engineering, Vol.35, No.4, pp. 293-298, 2020, DOI:10.32604/csse.2020.35.293

Abstract With the development of e-commerce, more and more enterprises attach importance to precision marketing for network channels. This study adopted the decision tree algorithm in data mining to achieve precision marketing. Firstly, precision marketing and C4.5 decision tree algorithm were briefly introduced. Then e-commerce enterprise A was taken as an example. The data from January to June 2018 were collected. Four attributes including age, income, occupation and educational background were selected for calculation and decision tree was established to extract classification rules.The results showed that the consumers of the products of the company were high-income young and middle-aged people, middle-income… More >

Jing-Hua Zhao^1,†, Da-Lin Zeng^2,*, Ting-Wei Zhou^1,‡, Ze-Chao Zhu^1,§

Computer Systems Science and Engineering, Vol.35, No.3, pp. 151-172, 2020, DOI:10.32604/csse.2020.35.151

Abstract Given the government subsidies for new energy vehicles, this study is conducted to study the closed-loop supply chain comprising individual manufacturers, individual retailers and individual third-party recyclers. In this paper, combine the reality of new energy vehicles with the relevant research of game theory, and establish an no government subsidy model (Model N), a government subsidized consumer model (Model C), a government subsidized manufacturer model (Model M), a government subsidized third party recycler model (Model T), and a government subsidized retailer model (Model R) for quantitative research. Then, numerical examples are used to simulate the impact of government subsidies on… More >

Bing Xu^1,∗, Darong Huang^2,†, Bo Mi^3,‡

Computer Systems Science and Engineering, Vol.35, No.2, pp. 113-121, 2020, DOI:10.32604/csse.2020.35.113

Abstract In this paper, according to the information classification algorithm in data mining, data in the network payment system of e-commerce is mined, forming an effective evaluation of the security of the network payment system. Firstly, the method of network security risk prediction is discussed. Secondly, according to the characteristics of network payment system, the system security index system is analyzed in detail, and the specific application process of the C4.5 Classification Algorithm in security evaluation is discussed. Finally, the data mining process is designed in detail and the corresponding code established. In this paper, data mining theory is applied to… More >

Alberto Fernández Oliva¹, Francisco Maciá Pérez², José Vicente Berná-Martinez^2,*, Miguel Abreu Ortega³

Computer Systems Science and Engineering, Vol.34, No.3, pp. 131-144, 2019, DOI:10.32604/csse.2019.34.131

Abstract This study presents a method for the detection of outliers based on the Variable Precision Rough Set Model (VPRSM). The basis of this model is the generalisation of the standard concept of a set inclusion relation on which the Rough Set Basic Model (RSBM) is based. The primary contribution of this study is the improvement in detection quality, which is achieved due to the generalisation allowed by the classification system that allows a certain degree of uncertainty. From this method, a computationally efficient algorithm is proposed. The experiments performed with a real scenario and a comparison of the results with… More >

Fanxiu Dong^*

Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 617-624, 2020, DOI:10.32604/iasc.2020.013940

Abstract At present, the allocation of the medical service resources is directed at a single service resource, and there are many unreasonable problems, which causes medical cost to be high. Based on this, the application of the DRGs and the fuzzy demand in the medical service resource allocation based on the data mining algorithm is proposed. The application research of the DRGs and the data mining algorithm is simply analyzed, then the uncertain demand estimation is applied to the fuzzy demand processing based on the fuzzy demand theory and the medical service resources are configured under the established demand satisfaction rate.… More >

Chen Yu^∗, Qinmin Hong, Dezhong Yao, Hai Jin

Computer Systems Science and Engineering, Vol.33, No.2, pp. 87-94, 2018, DOI:10.32604/csse.2018.33.087

Abstract The rapid expansion of GPS-embedded devices has showed the emerging new look of location-based services, enabling such offerings as travel guide services and location-based social networks. One consequence is the accumulation of a rich supply of GPS trajectories, indicating individuals’ historical position. Based on these data, we aim to mine the hot route by using a collaborative tensor calculation method. We present an efficient trajectory data processing model for mining the hot route. In this paper, we rst model the individual’s trajectory log, extract sources and destinations, use map matching to get the corresponding road segments, and nally apply the… More >

Sudan Jha¹, Gyanendra Prasad Joshi², Lewis Nkenyereya³, Dae Wan Kim^{4, *}, Florentin Smarandache⁵

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1203-1220, 2020, DOI:10.32604/cmc.2020.011618

Abstract Raw data are classified using clustering techniques in a reasonable manner to create disjoint clusters. A lot of clustering algorithms based on specific parameters have been proposed to access a high volume of datasets. This paper focuses on cluster analysis based on neutrosophic set implication, i.e., a k-means algorithm with a threshold-based clustering technique. This algorithm addresses the shortcomings of the k-means clustering algorithm by overcoming the limitations of the threshold-based clustering algorithm. To evaluate the validity of the proposed method, several validity measures and validity indices are applied to the Iris dataset (from the University of California, Irvine, Machine… More >

Uma K.V^1,*, Appavu alias Balamurugan S²

Intelligent Automation & Soft Computing, Vol.26, No.1, pp. 61-70, 2020, DOI:10.31209/2019.100000153

Abstract Real world data consists of lot of impurities. Entropy measure will help to handle impurities in a better way. Here, data selection is done by using Naïve Bayes’ theorem. The sample which has posterior probability value greater than that of the threshold value is selected. C5.0 decision tree classifier is taken as base and modified the Gain calculation function using Tsallis entropy and Association function. The proposed classifier model provides more accuracy and smaller tree for general and Medical dataset. Precision value obtained for Medical dataset is more than that of existing method. More >

Zheng Xu, Zhiguo Yan

Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 517-518, 2018, DOI:10.31209/2018.100000018

Abstract This article has no abstract. More >

Qian Wang^a,b,c, Jiadong Ren^a,b, Darryl N Davis^c, Yongqiang Cheng^c

Intelligent Automation & Soft Computing, Vol.24, No.2, pp. 399-404, 2018, DOI:10.1080/10798587.2017.1340135

Abstract Frequent pattern mining usually requires much run time and memory usage. In some applications, only the patterns with top frequency rank are needed. Because of the limited pattern numbers, quality of the results is even more important than time and memory consumption. A Frequent Pattern algorithm for mining Top-rank-K patterns, FP_TopK, is proposed. It is based on a Node-list data structure extracted from FTPP-tree. Each node is with one or more triple sets, which contain supports, preorder and postorder transversal orders for candidate pattern generation and top-rank-k frequent pattern mining. FP_ TopK uses the minimal support threshold for pruning strategy… More >