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International Conference on Mechatronics Engineering and Computing Technology (ICMECT)

作者： Xiao, Bing GuangDong Polytech Normal Univ Sch Comp Sci Guangzhou 510665 Guangdong Peoples R China

ISBN: (纸本)9783038351153

Through digging out the core suppliers and core customers from the numerous suppliers and customers in the complex network of E-commerce, it contributes to reducing the adverse selection for the consumers and moral hazards for the operators caused by information asymmetry. Meanwhile, it is very meaningful for the credit risk protection in the complex network of E-commerce. On the basis of the references to the White and Smyth algorithms, in this paper, improvements from the White and Smyth algorithms are made herein, combining several features of the E-commerce complex network such as competitiveness, incomplete information and unsymmetrical information. In addition, an algorithm for mining the key nodes in E-commerce complex network is put forward, and applications are explained by instances.

关键词： E-commerce complex network core node mining algorithm

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Audio service system and enterprise HRM deployment based on decision tree algorithm and network optimization

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2023年 1-9页

作者： Zhao, Yuxuan Changzhou Coll Informat Technol Human Resources Dept Changzhou 213164 Jiangsu Peoples R China

The development speed of modern society is getting faster and faster, and the accumulation of information and data is also increasing, so it is necessary to provide targeted information. The existing research has solved this problem well. This paper studies the relevant literature, introduces the classification algorithm in data mining in detail, studies the existing data mining algorithm from different angles, as well as their shortcomings in practical application. The incremental learning method is used to extract data in the mining algorithm, and a decision tree algorithm is proposed to solve the problem of the classical incremental decision tree, and the experimental data is analyzed. In addition, small and medium-sized enterprises are facing problems such as financial difficulties and insufficient human resources. This paper uses the network to realize the emergency configuration section of human resources, and optimizes its configuration process through the network. According to the relevant theories of the network and the special nature of human resources, a human resource grid deployment model is proposed. Using EDA tool, a low cost audio simulation system is designed and implemented, and the circuit synthesis is successfully realized. By improving the mining algorithm, exploring the audio service system, and putting forward suggestions for the deployment of human resources in enterprises, the research results of this paper have important practical application value.

关键词： Fuzzy data mining algorithm Audio service system Enterprise human resource deployment

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Feedback System Design of Architectural Planning Based on Diversified Hot mining algorithm

Feedback System Design of Architectural Planning Based on Di...

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International Conference on Advances in Materials Science and Information Technologies in Industry (AMSITI)

作者： Lv, Haijing Han, Zhenkun Northeast Agr Univ Sch Art Harbin 150031 Peoples R China Harbin Inst Technol Sch Architecture Harbin 150001 Peoples R China

ISBN: (纸本)9783038350125

Under the background of information era, we use WEB2.0, which has rich feedback system of users, to analyze the diversification of information transfer mode. It will make the performance results of the system more intelligent and systematization. Therefore, we use the manifestation of architecture planning art as an example, in the WEB2.0 environment, presents a multi hot spot mining algorithm, to analyze the diversification and individuation. We use the established transferring model to do data modeling. Then extracting and evaluating the content of text. The experimental results show that the data hot mining algorithm based on diversification can use the feedback information of users effectively, adapting to the WEB2.0 environment. Therefore, in the spreading development of internet information today, based on the internet resources, this paper presents a new algorithm to analyze diversification and individuation manifestation of architecture planning art. It provides a technical innovation and theoretical reference.

关键词： Internet Architecture planning Diversification WEB service mining algorithm

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Fuzzy Clustering Analysis of Power Incomplete Data based on Improved IVAEGAN Model

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2022年第7期13卷 207-214页

作者： Hong, Yutian Lin, Jun Guangdong Elect Power Informat Technol Co Ltd Guangzhou 520000 Guangdong Peoples R China

The scale of data generated by the complex and huge power system during operation is also very large. With the data acquisition of various information systems, it is easy to form the situation of incomplete power data information, which cannot guarantee the efficiency and quality of work, and reduce the security and reliability of the entire power grid. When incomplete data and incomplete data sets are caused by data storage failure or data acquisition errors, fuzzy clustering of data will face great difficulties. The fuzzy clustering of incomplete data of the power equipment is divided into the processing of incomplete data and the clustering analysis of "recovered " complete data. This paper proposes an IVAEGAN-IFCM interval fuzzy clustering algorithm, which uses interval data sets to fill in the incomplete data, and then completes the clustering of interval data. At the same time, the whole numerical data set is transformed into a complete interval data set. The final clustering result is obtained by interval fuzzy mean clustering analysis of the whole interval data set. Finally, the algorithm proposed in this paper and other machine learning training data sets is made for experimental analysis. The experimental results show that the algorithm proposed in this paper can complete incomplete data sets with high precision clustering. Compared with other contrast methods, it shows higher clustering accuracy. Compared with the numerical clustering algorithm, the clustering accuracy is improved by more than 4.3%, and it has better robustness. It also shows better generalization on the artificial data sets and other complex data sets. It is helpful to improve the technical level of the existing power grid and has important theoretical research value and engineering practice significance.

关键词： Power system power equipment incomplete data fuzzy clustering mining algorithm

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An Efficient Search Space Exploration Technique for High Utility Itemset mining

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Procedia Computer Science 2023年 218卷 937-948页

作者： Suresh B Patel Sanjay M Shah Mahendra N Patel PhD Scholar Gujarat Technological University Ahmedabad India Computer Engineering L.D.C.E Ahmedabad India Information Technology Department GEC Gandhinagar Gujarat-India-380028

Data mining techniques discover the potentially helpful pattern concealed in a vast database for the decision support system in various real-life applications. One such technique is association rule mining. It finds the pattern from the transaction database to understand customer behavior. Frequent itemset mining (FIM) identifies a set of frequently purchased items together. One key drawback of FIM is that it ignores the item's importance. An item's importance plays a pivotal role in a real-world application. Therefore, it is necessary to discover the essential itemset from the transaction database that generate the high profit called the HUIM (High-Utility Itemset mining) problem. From a transaction database, a variety of strategies can be used to find high utility itemset. The HUIM techniques that use the Utility list are recent and have better performance in terms of memory utilization and running time. The key limitation of these algorithms is performing costly utility list join operations. This paper proposes an efficient search space exploration technique to lessen the number of comparisons performed for utility list join operations. Hence, it reduces the cost of utility list join operations. In addition, the execution time of the proposed method is evaluated. Further, the same is compared with appropriate existing state-of-the-art methods. Finally, extensive experiments carried out on publicly available benchmark datasets show that the proposed support count ascending order (SCAO) based approach performs much better as oblivious to the state-of-the-art methods.

关键词： mining algorithm High utility itemset mining pattern utility-list Transaction weighted utity

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Research on the Application of Chaotic Iteration Function of Heterogeneous Populations mining algorithm in Computer Based On Co-Evolution

Research on the Application of Chaotic Iteration Function of...

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第四届智能结构与振动控制国际会议

作者： Han Zheng Xiaobo Gao School of Computer and Information Engineering Hechi University

Based on the co-evolution theory,this paper establishes the mathematical model of heterogeneous populations,and joins the chaos function concept in the model,which makes the function have the effect of turning iterative nature of chaos,and designs computer digital output *** order to study the validity and reliability of the designed algorithm and mathematical model in this paper,with the combination of BSIM3 and MOSFET model,the paper designs a computer automatic control circuit,and the circuit is studied by numerical *** Md-Vds curve can be seen that the numerical simulation result is consist with experimental results,which verify the validity of the *** computer control circuit I-VTH characteristic curve can be seen that the peak value of circuit fluctuation is consisting with the theoretical situation,which verified the reliability of the algorithm.

关键词： Co-Evolution Heterogeneous Populations mining algorithm Chaos Iteration MOSFET I-VTH Characteristic Curve

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Improved community structure discovery algorithm based on combined clique percolation method and K-means algorithm

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PEER-TO-PEER NETWORKING AND APPLICATIONS 2020年第6期13卷 2224-2233页

作者： Zhou, Zhou Xiao, Zhuopeng Deng, WeiHong Changsha Univ Dept Math & Comp Sci Changsha 410083 Peoples R China Zhangjiajie Inst Aeronaut Engn Informat Engn Dept Zhangjiajie 427000 Peoples R China

Research on the community structure of networks is beneficial for understanding the structure of networks, analyzing their characteristics and discovering the rules hidden in these networks. To address issues from previous community mining algorithms, such as the low rate of convergence and high time complexity, this study proposes an improved community structure discovery algorithm named CPMK-Means algorithm. The main idea of this algorithm can be summarised as follows. The clique percolation method (CPM) algorithm generates the maximum number of cliques by combining depth-first search with breadth-first search so that the number of cluster centres is determined. Then, the k centres are selected based on the principle of the maximum degree of centres and minimum similarity between different centres. Afterwards, nodes in the network are assigned to the communities formed by the k centres, and the iterations are performed repeatedly until the centres become stable. Finally, the overlapping communities are merged. Experiments are carried out on standard data sets Football and Collins to evaluate the performance of the CPMK-Means algorithm. Results indicate that the CPMK-Means algorithm can achieve better community mining and higher execution efficiency compared with other algorithms. Furthermore, it is superior to other algorithms in terms of precision, recall, accuracy, F-measure and separation.

关键词： Big data Parallel computing Community structure Execution efficiency mining algorithm

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Research Of A mining algorithm Based On Markov Chain On WEB Page Access Sequence Features

Research Of A Mining Algorithm Based On Markov Chain On WEB ...

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International Conference on Information Technology and Applications (ITA)

作者： Liu, Gang Guo, Han Jilin Inst Architecture & Engn Changchun Peoples R China Changchun Univ Technol Changchun Peoples R China

ISBN: (纸本)9781479928767

Web access to sequence data mining to help improve the quality of Web access, the sequence is a difficult problem in data mining, the prevalence of classic sequential algorithm and storage space overhead is too large defects. Web access sequence mining algorithm based on Markov chain can be found through less computation requests a web page. And for the design of the site, and achieved good results. Recognize that the most likely path through the site through the Web click-stream in order to predict the users will want to browse web pages, and accordingly to improve the design and construction of the site. Less computation to find the requested page, optimization of the hyperlink structure of the Web site.

关键词： Markov Chain mining algorithm WEB Transfer Matrix

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mining Accompanying Passing-Vehicles to Discover Suspected Gangs 19

Mining Accompanying Passing-Vehicles to Discover Suspected G...

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19th IEEE International Symposium on High Assurance Systems Engineering (HASE)

作者： Wei Zhihao Li Jianyuan Li Wanqing Hangzhou Dianzi Univ Sch Comp Sci & Technol Hangzhou Zhejiang Peoples R China Inst Enjoyor Co Ltd Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781538685402

The accompanying vehicles usually provide valuable hints to discover the suspected gangs.. In this paper, using Hadoop, a new and efficient algorithm named TMFS is proposed for mining the spatial-and-temporal accompanying vehicles accurately and rapidly. Compared with the traditional algorithms, the veracity, run time and memory usage are all discussed in detail. Experimental results show that the Traffic MapReduced by Frequent Sequences (TMFS) algorithm is superior to Apriori algorithm and BIDE algorithm.

关键词： component Data mining Accompanying Passing-Vehicles Hadoop mining algorithm

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Fuzzy comprehensive evaluation of physical education based on high dimensional data mining

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JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2018年第3期35卷 3065-3076页

作者： Wang, Zhihui Inner Mongolia Univ Nationalities Coll Phys Educ Tongliao 028043 Peoples R China

The spectrum cluster algorithm is opposite in the other cluster algorithm has the obvious superiority that can distinguish the non-raised distribution the cluster, suits extremely in many actual problems. With this prior model this paper combines the fuzzy set system to propose the new data mining algorithm. At the same time, we build a fuzzy comprehensive evaluation model and analyze the evaluation system of physical education. The result shows that the fuzzy comprehensive evaluation method is improved by using the grey relational grade, which avoids the disadvantages of adopting the principle of maximum membership degree. Therefore, this evaluation method can be used in the evaluation of public sports teaching in colleges and universities.

关键词： mining algorithm grey system public physical education high dimensional data fuzzy comprehensive evaluation

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