scholarly journals Analysis of the Impact of Big Data on E-Commerce in Cloud Computing Environment

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Rongrui Yu ◽  
Chunqiong Wu ◽  
Bingwen Yan ◽  
Baoqin Yu ◽  
Xiukao Zhou ◽  
...  
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Data Storage ◽  
Large Scale ◽  
Query Language ◽  
Optimal Path ◽  
Data Mining Algorithm ◽  
Advantages And Disadvantages ◽  
Mining Algorithm ◽  
The Impact

This article starts with the analysis of the existing electronic commerce system, summarizes its characteristics, and analyzes and solves its existing problems. Firstly, the characteristics of the relational database My Structured Query Language (MySQL) and the distributed database HBase are analyzed, their respective advantages and disadvantages are summarized, and the advantages and disadvantages of each are taken into account when storing data. My SQL is used to store structured business data in the system, while HBase is used to store unstructured data such as pictures. These two storage mechanisms together constitute a data storage subsystem. Secondly, considering the large amount of data in the e-commerce system and the complex calculation of the data mining algorithm, this paper uses MapReduce to realize the parallelization of the data mining algorithm and builds a Hadoop-based commodity recommendation subsystem on this basis. We use JavaEE technology to design a full-featured web mall system. Finally, based on the impact of cloud computing, mobile e-commerce is analyzed, including relevant theories, service mode, architecture, core technology, and the application in e-commerce, which can realize e-commerce precision marketing, find the optimal path of logistics, and take effective security measures to avoid transaction risks. This method can avoid the disadvantages of the traditional e-commerce, where large-scale data cannot be processed in a timely manner, realize the value of mining data behind, and realize the precision marketing of e-commerce enterprises.

A Review: Map Reduce Framework for Cloud Computing

2018 ◽  
Vol 7 (4.6) ◽  
pp. 13
Author(s):  
Mekala Sandhya ◽  
Ashish Ladda ◽  
Dr. Uma N Dulhare ◽  
. . ◽  
. .
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Distributed Computing ◽  
Data Storage ◽  
High Performance ◽  
Large Scale ◽  
Distributed Storage ◽  
Large Data ◽  
Mass Data ◽  
Internet Information

In this generation of Internet, information and data are growing continuously. Even though various Internet services and applications. The amount of information is increasing rapidly. Hundred billions even trillions of web indexes exist. Such large data brings people a mass of information and more difficulty discovering useful knowledge in these huge amounts of data at the same time. Cloud computing can provide infrastructure for large data. Cloud computing has two significant characteristics of distributed computing i.e. scalability, high availability. The scalability can seamlessly extend to large-scale clusters. Availability says that cloud computing can bear node errors. Node failures will not affect the program to run correctly. Cloud computing with data mining does significant data processing through high-performance machine. Mass data storage and distributed computing provide a new method for mass data mining and become an effective solution to the distributed storage and efficient computing in data mining. 

Research on Association Rule Mining Algorithm Based on Distributed Data

2014 ◽  
Vol 998-999 ◽  
pp. 899-902 ◽  
Author(s):  
Cheng Luo ◽  
Ying Chen
Keyword(s):  
Data Mining ◽  
Association Rule ◽  
Association Rule Mining ◽  
Large Scale ◽  
Frequent Itemsets ◽  
Network Communication ◽  
Data Mining Algorithm ◽  
Distributed Data ◽  
Rule Mining ◽  
Mining Algorithm

Existing data miming algorithms have mostly implemented data mining under centralized environment, but the large-scale database exists in the distributed form. According to the existing problem of the distributed data mining algorithm FDM and its improved algorithms, which exist the problem that the frequent itemsets are lost and network communication cost too much. This paper proposes a association rule mining algorithm based on distributed data (ARADD). The mapping marks the array mechanism is included in the ARADD algorithm, which can not only keep the integrity of the frequent itemsets, but also reduces the cost of network communication. The efficiency of algorithm is proved in the experiment.

scholarly journals Human Resource Allocation Based on Fuzzy Data Mining Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
You Wu ◽  
Zheng Wang ◽  
Shengqi Wang
Keyword(s):  
Data Mining ◽  
Human Resource ◽  
Business Process ◽  
Association Rule ◽  
Association Rule Mining ◽  
Large Scale ◽  
Data Mining Algorithm ◽  
Rule Mining ◽  
Mining Algorithm ◽  
Database Technology

Data mining is currently a frontier research topic in the field of information and database technology. It is recognized as one of the most promising key technologies. Data mining involves multiple technologies, such as mathematical statistics, fuzzy theory, neural networks, and artificial intelligence, with relatively high technical content. The realization is also difficult. In this article, we have studied the basic concepts, processes, and algorithms of association rule mining technology. Aiming at large-scale database applications, in order to improve the efficiency of data mining, we proposed an incremental association rule mining algorithm based on clustering, that is, using fast clustering. First, the feasibility of realizing performance appraisal data mining is studied; then, the business process needed to realize the information system is analyzed, the business process-related links and the corresponding data input interface are designed, and then the data process to realize the data processing is designed, including data foundation and database model. Aiming at the high efficiency of large-scale database mining, database development tools are used to implement the specific system settings and program design of this algorithm. Incorporated into the human resource management system of colleges and universities, they carried out successful association broadcasting, realized visualization, and finally discovered valuable information.

scholarly journals Multimedia Computer-Aided Industrial System Design Based on the Study of Big Data Mining Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Zhihao Zeng
Keyword(s):  
Data Mining ◽  
Big Data ◽  
System Design ◽  
Data Mining Algorithm ◽  
Industrial System ◽  
Overall Design ◽  
Big Data Mining ◽  
Mining Algorithm ◽  
Computer Aided ◽  
The Impact

Aiming at the problems of the multimedia computer-aided industrial system, this paper puts forward the application of big data mining algorithm to multimedia computer-aided industrial system design and analyzes in detail the impact of multimedia technology on industrial quality. This paper introduces the advantages of using big data mining algorithm in multimedia computer technology course, shows the operating environment to be met by using the multimedia computer-aided industrial system, follows the guiding principles of the overall design learning theory and artistic conception cognition theory, supplements specific industrial examples, and discusses multimedia industrial design.

scholarly journals Analysis of the Mental Health of Urban Migrant Children Based on Cloud Computing and Data Mining Algorithm Models

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Juan Li
Keyword(s):  
Mental Health ◽  
Data Mining ◽  
Cloud Computing ◽  
Urban Children ◽  
Migrant Children ◽  
Current Status ◽  
Data Mining Algorithm ◽  
Mining Algorithm ◽  
Urban Migrant ◽  
The City

With the rapid development of internet technology, the amount of data generated is also increasing day by day. As a kind of distributed computing, cloud computing has been widely used in the analysis of massive data. With the development of China’s economic construction, the integration of urban and rural areas is constantly improving, and the migrant children in the city are also focused on. After moving into the city, migrant children not only face the pressure from the society but also face the pressure from life, which inevitably affects the physical and mental health of urban migrant children. The education of urban migrant children is also a focus that needs attention. How to integrate into the education environment of urbanization and adjust the learning pressure in the process of education is also worthy of our attention. Therefore, this article analyzes the current status of urban migrant children’s mental health based on cloud computing and data mining algorithm models. Based on the current research status of urban migrant children and the standards of mental health, this paper conducts a survey of middle and high school students in a certain city through questionnaires, then builds a data mining algorithm model to analyze the survey data, and explores the differences in the grades of students’ social identity and the differences in mental health between migrant children and urban children. According to the survey, most of the psychological performances of urban migrant children are very vague. At the same time, there are also some phenomena such as poor adaptability, bad mood, and inferiority complex. During the study period, there are situations such as unwilling to communicate with others, weariness, sensitivity, anxiety, and hostility. The overall incidence of the situation is relatively high in big cities, while the situation of urban children is relatively small.

A Study on Improved Eclat Data Mining Algorithm

2011 ◽  
Vol 328-330 ◽  
pp. 1896-1899 ◽  
Author(s):  
Zhi Fang Li ◽  
Xiu Fang Liu ◽  
Xu Cao
Keyword(s):  
Data Mining ◽  
Data Mining Algorithm ◽  
Advantages And Disadvantages ◽  
Mining Algorithm

An introduction on the algorithm Apriori and FP-growth is given. And their advantages and disadvantages are pointed out. The rule of mining transaction databases has two common formats, horizontal layout and vertical layout. Normally, algorithm using vertical database layout is often superior to those using horizontal layout. A new Eclat algorithm was brought out, which is an improvement of Eclat and show good performance with a lot of datasets.

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