Research on the Improvement of Data Mining Algorithm Based on “Internet +” System in Cloud Computing

2020 ◽  
Author(s):  
Jia Yu
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Data Mining Algorithm ◽  
Mining Algorithm

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.

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.

scholarly journals DATA MINING ALGORITHM BASED ON CLOUD COMPUTING

2018 ◽  
Vol 48 (4) ◽  
pp. 281-285
Author(s):  
Y. J. HAO
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Cellular Neural Network ◽  
Data Mining Algorithm ◽  
Computing Technology ◽  
Data Mining Algorithms ◽  
Mining Algorithm ◽  
Hash Algorithm ◽  
Mining Algorithms ◽  
Big Data Technology

The data mining algorithm based on cloud computing is studied and analyzed in this paper. Firstly, the research status and background of the data mining algorithms based on cloud computing are introduced briefly. Secondly, the design of Hash algorithm under cellular neural network is introduced which is needed in this paper. Next, the design of wavelet data compression algorithm for wireless sensor networks is described. Finally, the experimental results and the optimization similarity analysis are obtained. The analysis results show that the data mining algorithm based on cloud computing constructed in this paper plays an important role in data mining, and can improve the data mining algorithm of cloud computing and the development level of cloud computing technology and big data technology to some extent.

scholarly journals Secure Multi-User k-Means Clustering Based on Encrypted IoT Data

2019 ◽  
Vol 12 (2) ◽  
pp. 35
Author(s):  
Yanling Li ◽  
Chuansheng Wang ◽  
Qi Wang ◽  
Jieling Dai ◽  
Yushan Zhao
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Theoretical Analysis ◽  
Knowledge Discovery ◽  
Data Mining Algorithm ◽  
Personal Privacy ◽  
Encrypted Data ◽  
Mining Algorithm ◽  
Public Keys ◽  
Semantic Security

IoT technology collects information from a lot of clients, which may relate to personal privacy. To protect the privacy, the clients would like to encrypt the raw data with their own keys before uploading. However, to make use of the information, the data mining technology with cloud computing is used for the knowledge discovery. Hence, it is an emergent issue of how to effectively performing data mining algorithm on the encrypted data. In this paper, we present a k-means clustering scheme with multi-user based on the IoT data. Although, there are many privacy-preserving k-means clustering protocols, they rarely focus on the situation of encrypting with different public keys. Besides, the existing works are inefficient and impractical. The scheme we propose in this paper not only solves the problem of evaluation on the encrypted data under different public keys but also improves the efficiency of the algorithm. It is semantic security under the semi-honest model according to our theoretical analysis. At last, we evaluate the experiment based on a real dataset, and comparing with previous works, the result shows that our scheme is more efficient and practical.

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