scholarly journals Optimization of the Marketing Management System Based on Cloud Computing and Big Data

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Lin Zhang
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Rapid Development ◽  
Social Economy ◽  
Mobile Internet ◽  
Attribute Selection ◽  
Marketing System ◽  
Mining Technology ◽  
Internet Applications ◽  
Attribute Analysis

With the rapid development of the Internet information age, social networks, mobile Internet, and e-commerce have expanded the scope of Internet applications. The “big data” era is a challenge and chance for companies and has a great impact on social economy, politics, culture, and people’s lives. An accurate marketing system is developed based on J2EE, and the architecture is selected from the user layer, business logic layer, and data layer and the B/S3 layer application (three-tier application), including three layers of crip-dm and semma. And, other process methods are used. Data-mining-based marketing system information solutions consist of several parts, such as requirement analysis, design, implementation, and testing. This paper introduces data mining technology to the marketing business based on the practical use and design IT solutions for precision marketing, attribute selection tools, attribute analysis tools, modeling prediction tools, and others. This paper introduces a precision marketing system based on data mining technology. The system passes the actual test and the deployment and the operation of this system are confirmed. The system, which can improve marketing activity, is tested, and the development and operation of this system markedly increase the company’s earnings.

scholarly journals Research on Big Data Computing Model based on Spark and Big Data Application

2021 ◽  
Vol 2082 (1) ◽  
pp. 012017
Author(s):  
Sida Chen
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Rapid Development ◽  
Social Economy ◽  
Computing System ◽  
Big Data Mining ◽  
New Thinking ◽  
Big Data Application ◽  
Data Ecosystem ◽  
Internet Of Things Technology

Abstract Under the background of the information age, with the rapid development of cloud computing and Internet of things technology, all kinds of data information grow rapidly. How to transform massive data information into effective resources is the key point of big data technology research. This paper introduces the inherent laws of big data mining technology, determine and use valuable information data, which can open a new thinking and cognitive perspective, and it is of great significance to the development of the social economy. It can be concluded that the big data ecosystem based on spark platform and application of big data still have a lot of room for development, but there are also some problems. Nowadays, as a low latency cluster distributed computing system for big data collection, spark platform can provide more support for improving the efficiency of big data mining, but some of its methods are not perfect.

scholarly journals Precise Position Intelligent Matching System of Online Recruitment Platform Based on Data Mining Technology

2021 ◽  
Vol 2066 (1) ◽  
pp. 012001
Author(s):  
Zhen Gao
Keyword(s):  
Data Mining ◽  
Rapid Development ◽  
Internet Technology ◽  
Job Seekers ◽  
Mining Technology ◽  
Position Information ◽  
Precise Position ◽  
Random Mass ◽  
Online Recruitment ◽  
Platform System

Abstract With the rapid development of Internet technology and computer technology, network applications have been developed more and more, and have penetrated into all walks of life in society. The emergence of the networking of the talent market has made the scale of online recruitment increase, and the amount of data on the Internet has become larger and larger, and online recruitment has become the main channel for corporate recruitment. Therefore, how to use the massive online recruitment data to quickly and accurately find the corresponding information and explore the hidden knowledge mode is a very valuable research topic. Data mining (DM) is a technology for data analysis for large amounts of data. It can discover hidden, hidden, and potentially useful knowledge hidden in the data from the vague, noisy, and random mass data, and build relevant Model, realize prediction, etc. The characteristics of data mining technology (DMT) are very suitable for the analysis of online recruitment information, research on large amounts of information, and find out the knowledge in it for decision support. This article aims to study the accurate job matching system of the online recruitment platform based on DMT. Based on the analysis of the advantages of online recruitment, related DMT and the design principles of the online recruitment platform system, the data collected by Weka DM tools are analyzed. Analyzing and getting useful job positions is just to provide job seekers and corporate-related recruiters with useful job information. The experimental results show that the online recruitment platform system can complete the collection of online recruitment position information, and can realize the DM function, which has good practical application value.

Big data based research on the management system framework of ideological and political education in colleges and universities

2020 ◽  
pp. 1-10
Author(s):  
Yuejun Xia
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Big Data ◽  
Ideological And Political Education ◽  
Political Education ◽  
Representative Point ◽  
Point Sets ◽  
Mining Technology ◽  
Education Management ◽  
Intelligence System

Artificial intelligence model combined with data mining technology can mine useful data from college ideological and political education management, and conduct process evaluation and teaching management. Therefore, based on the superiority of data mining technology and artificial intelligence system, this paper improves the traditional algorithm and constructs a university ideological and political education management model based on big data artificial intelligence. Moreover, this study uses a local sensitive hash function to generate representative point sets and uses the generated representative point sets for clustering operations. In order to verify the performance of the algorithm model, a control experiment is designed to compare the algorithm of this paper with traditional data mining methods. It can be seen from the research results that the algorithm model constructed in this paper has good performance and can be applied to practice.

scholarly journals Improvement of Support Vector Machine Algorithm in Big Data Background

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Babacar Gaye ◽  
Dezheng Zhang ◽  
Aziguli Wulamu
Keyword(s):  
Machine Learning ◽  
Data Mining ◽  
Big Data ◽  
Time Complexity ◽  
Dual Problem ◽  
Learning Algorithm ◽  
Rapid Development ◽  
Machine Learning Algorithms ◽  
Support Vector ◽  
Original Space

With the rapid development of the Internet and the rapid development of big data analysis technology, data mining has played a positive role in promoting industry and academia. Classification is an important problem in data mining. This paper explores the background and theory of support vector machines (SVM) in data mining classification algorithms and analyzes and summarizes the research status of various improved methods of SVM. According to the scale and characteristics of the data, different solution spaces are selected, and the solution of the dual problem is transformed into the classification surface of the original space to improve the algorithm speed. Research Process. Incorporating fuzzy membership into multicore learning, it is found that the time complexity of the original problem is determined by the dimension, and the time complexity of the dual problem is determined by the quantity, and the dimension and quantity constitute the scale of the data, so it can be based on the scale of the data Features Choose different solution spaces. The algorithm speed can be improved by transforming the solution of the dual problem into the classification surface of the original space. Conclusion. By improving the calculation rate of traditional machine learning algorithms, it is concluded that the accuracy of the fitting prediction between the predicted data and the actual value is as high as 98%, which can make the traditional machine learning algorithm meet the requirements of the big data era. It can be widely used in the context of big data.

scholarly journals Influence of Healthy Physical Fitness on the Teaching of Aerobics Course Based on Big Data Mining Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Laipeng Xiao
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Physical Fitness ◽  
Physical Training ◽  
Body Shape ◽  
Teaching Experiment ◽  
The Body ◽  
Mining Technology ◽  
Big Data Mining ◽  
The Impact

Healthy physical fitness is one of the hot topics discussed by scholars at home and abroad in recent years, and it is a key indicator for evaluating students’ physical function and body shape. Aerobics, also known as bodybuilding, means that the body and health of students should have a better promotion effect, but in reality, many students found that after elective aerobics, body shape and health level basically did not improve, which is related to the setting of aerobics courses, especially the lack of physical training. Aerobics and other sports have common requirements in physical training, such as strength quality, speed quality, endurance quality, agility quality, and flexibility quality. This article is aimed at studying the impact of healthy physical fitness based on big data mining technology on the teaching of aerobics. On the basis of analyzing the process of data mining, the composition of healthy physical fitness, and the role of aerobics, it is used to test students in a certain university through experimental methods and statistical methods. Carry out aerobics teaching experiment, and compare and analyze the data measured by the experimental samples. The experimental results show that the use of healthy physical fitness in aerobics teaching can effectively promote the learning and improvement of aerobics skills.

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