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

Lin Zhang,Zhihan Lv

doi:10.1155/2021/9924302

Abstract

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.

Highlights

In recent years, the competition in the gaming industry has become more and more intense, and at the same time, game players have higher and higher requirements for game quality and game services
In the current game market, the early marketing methods are unsustainable, and major operators should devote themselves to solving the problems of “how to accurately locate target users,” “how to quickly discover the characteristics of user groups,” and “how to reduce the disturbance to nontarget users.” e operators should focus on solving the problems of “how to accurately locate target users,” “how to quickly discover the characteristics of user groups,” “how to reduce the disturbance to nontarget users,” and “how to improve user experience” [3]
From the application point of view, data-based operation can push games that users like to users from a wide variety of online games and avoid promoting those online games to users that are not interested, so as to improve the user experience based on those two aspects and establish good interaction [4]

Summary

Related Work

The mainstream research directions can be divided into two categories: the first is developing new algorithms and updating existing designs, and the second is exploring commercial applications of existing methods in the form of, for example, precision marketing business [14]. After consumers buy one kind of goods, they usually tend to buy another kind of goods, and this becomes a marketing concern, so a more reasonable marketing list should be developed Research directions in this area include the following: first, the study of association, which identifies goods as one-time purchases and analyzes the association between various goods, and second, the study of sequential problems, which analyzes the existence of time intervals in users’ purchasing behavior, while paying attention to the temporal connections. Incorporating the idea of semisupervised learning, the PC_SEM algorithm is proposed. e algorithm uses the partial constraint information that can be automatically obtained through the dataset to guide the clustering process, which makes the efficiency of probabilistic clustering of large-scale datasets and the quality of clustering results further improved [22, 23]

General Architecture Based on Data Mining

Results evaluation

System Optimization Test