scholarly journals Construction of an Intelligent Analysis Model for Website Information Based on Big Data and Cloud Computing Technology

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Ronghua Chen ◽  
Bei Yang
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Data Collection ◽  
Real Time ◽  
Delivery System ◽  
Pearson Correlation ◽  
System Optimization ◽  
Practical Significance ◽  
Computing Technology ◽  
Intelligent Analysis

Based on big data and cloud computing technology, the development process of this system includes hardware cluster deployment of the delivery system, optimization of website delivery strategy, and development of the delivery management background system. The main functions in the following aspects are realized: first, we built the website back-end delivery subsystem and data collection and analysis subsystem to realize the control of website delivery and data collection; second, we designed and developed a process management subsystem for booking, management, and delivery of website resources and developed the contract management and order management subsystems to realize the accurate placement of user portraits on the website; then, the placement data monitoring and effect feedback subsystems, and the data inventory subsystem of the website system were designed and developed. Finally, based on the research of Android and based on the Eclipse platform, this article has completed the construction of the Android 4.0.3 version environment, successfully used the Java development language to develop a website information intelligent analysis and navigation system, and analyzed the various functional modules of the entire system. Experimental results show that the system not only realizes ordinary route and site query functions but also combines map API, integrates big data and cloud computing technology, and realizes congestion avoidance query, time optimal query, population heat map, and real-time viewing. The nearby use of this software’s personnel density distribution and other functions provides great convenience for personal travel, which can facilitate the real-time planning of travel plans, and has great practical and practical significance. Through the different levels of testing of various subsystems, the website delivery system meets the functional and nonfunctional requirements proposed by the network and on this basis realizes the use of group wisdom based on Pearson correlation coefficient, Cosine similarity, and Tanimoto coefficient for collaborative filtering website recommendation algorithm.

Trends and Technologies in Big Data Processing

2020 ◽  
pp. 17-42
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Computing Technology ◽  
Time Data ◽  
Big Data Processing ◽  
Real Time Data ◽  
Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

Trends and Technologies in Big Data Processing

2021 ◽  
pp. 42-67
Author(s):  
Amitava Choudhury ◽  
Kalpana Rangra
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Data Processing ◽  
Real Time ◽  
Computing Technology ◽  
Time Data ◽  
Big Data Processing ◽  
Real Time Data ◽  
Real Time Data Processing

Data type and amount in human society is growing at an amazing speed, which is caused by emerging new services such as cloud computing, internet of things, and location-based services. The era of big data has arrived. As data has been a fundamental resource, how to manage and utilize big data better has attracted much attention. Especially with the development of the internet of things, how to process a large amount of real-time data has become a great challenge in research and applications. Recently, cloud computing technology has attracted much attention to high performance, but how to use cloud computing technology for large-scale real-time data processing has not been studied. In this chapter, various big data processing techniques are discussed.

A CNC Equipment Distributed Monitoring System Based on Cloud Computing Technology

2014 ◽  
Vol 1022 ◽  
pp. 392-395 ◽  
Author(s):  
Rang Yong Zhang ◽  
Geng Ma ◽  
Guang He Cheng
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Wireless Network ◽  
Monitoring System ◽  
Communication Technology ◽  
Wide Area ◽  
Distributed Monitoring ◽  
Real Time Monitoring ◽  
Computing Technology ◽  
Remote Diagnostics

CNC equipment distributed monitoring system based on cloud computing technology provides a sable and reliable remote real time monitoring system to monitoring a mount of CNC equipment distributed in a large wide area by wireless network and GPRS communication technology which can be used to remote diagnostics and improve service respond speed.

Research of Association Rules Algorithm Based on Matrix under Cloud Computing

2014 ◽  
Vol 568-570 ◽  
pp. 798-801
Author(s):  
Ye Qing Xiong ◽  
Shu Dong Zhang
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Big Data ◽  
Association Rules ◽  
Apriori Algorithm ◽  
Computing Technology ◽  
Binary Matrix ◽  
Transaction Data ◽  
Big Data Mining ◽  
Parallel Mining

It occurs time and space performance bottlenecks when traditional association rules algorithms are used to big data mining. This paper proposes a parallel algorithm based on matrix under cloud computing to improve Apriori algorithm. The algorithm uses binary matrix to store transaction data, uses matrix "and" operation to replace the connection between itemsets and combines cloud computing technology to implement the parallel mining for frequent itemsets. Under different conditions, the simulation shows it improves the efficiency, solves the performance bottleneck problem and can be widely used in big data mining with strong scalability and stability.

Origin Fresh Beer Remote Delivery System Based on Cloud Computing Technology

2014 ◽  
Vol 678 ◽  
pp. 126-129
Author(s):  
Geng Ma ◽  
Rang Yong Zhang
Keyword(s):  
Cloud Computing ◽  
Service Quality ◽  
Response Time ◽  
Delivery System ◽  
Supply System ◽  
Computing Technology

By introducing computing technology into origin beer remote delivery system, it solved beer producer’s problems of how to sell their origin fresh beer to the client thousands of miles away without losing it's quality. This way can greatly improve seller’s service quality and reduce response time of supply system comparing to traditional delivery system.

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