网络游戏客户管理系统的设计与实现

发布时间：2018-03-24 14:44

本文选题：数据挖掘　切入点：网络游戏　出处：《电子科技大学》2013年硕士论文

【摘要】：当前，计算机网络不断普及，网络游戏产品的品种和规模也越来越大，游戏玩家们可以选择的游戏种类和游戏公司也越来越多，相对而言就是网络游戏公司之间以及不同公司相同种类的网络游戏之间的竞争也越来越激烈。这就要求网络游戏公司要充分分析网络游戏客户的更多信息，不断的提高客户的满意程度，加深客户对游戏以及游戏公司的忠诚度。使得网络游戏公司能够占有很大的市场份额，获取更多的利润，已经成为每个网络游戏企业所面临的首要问题。由于国内的网络游戏企业发展的时间比较晚，在客户管理方面与国外的网络游戏公司还存在很大的差距。目前，我国的中小型网络游戏企业的客户管理比较松散，很多公司并没有科学的制定高级客户信息系统，无法对客户信息进行有效的管理。有的公司即使有客户管理系统，其系统所实现的仅仅是一些简单的客户信息的管理，均不具有网络游戏客户信息分析的功能。数据挖掘技术旨在寻找复杂数据中隐含于其内的隐含信息与知识，可以帮助企业制定客户管理上相关的决策。将数据挖掘中的先进方法应用于网络游戏的客户关系管理之，根据客户属性来划分客户的类别，进而建立起一对一的客户服务体系，进而根据客户所属类别，网络游戏运营商能够进行差异化的管理。本文将自组织映射神经网络技术用于研究了网络游戏客户的自动分类，对客户进行关系管理与分类，，设计了自组织映射神经网络聚类算法。通过对本课题的研究，将基于数据挖掘的客户关系管理理念引入网络游戏企业，同时建立一个适合网络游戏企业的客户关系管理系统。该系统可以完成客户管理、客户基本信息管理、客户分类、统计分析与打印等功能。论文详细的分析了系统的整体设计、数据流图，以及各个子模块的设计，给出详细的设计与实现过程。对所设计的网络游戏客户关系管理系统进行测试，测试结果说明：本系统不但可以按照客户的差别进行分类，而且还可以按照客户待发掘的潜力进行分析。通过本系统可以不断提高客户的保有率，并且可以挖掘潜在客户的潜力市场，全面提高游戏企业的利润和市场竞争力。
[Abstract]:At present, the computer network popularization, the network game product variety and scale is also growing, game player can choose the types of games and game companies are more and more, among the relatively is the network game companies and different companies of the same kind of network game has become increasingly fierce competition. This requires the network game company the full analysis of more information network game customers, continuously improve customer satisfaction, enhance customer loyalty to the game and the game company. The network game company can occupy the market share of large, gain more profit, has become the primary problem of each network game enterprises. Due to the development of the domestic online game companies later, there is a big gap between the network game company customer management in and abroad. At present, China's small and medium-sized Customer management network game business is relatively loose, many companies did not develop advanced customer information system of science, it cannot effectively manage customer information. Some companies even have a customer management system, the implementation of the system is only a simple customer information management, network game has no customer information analysis function.
The data mining technology to find complex data hidden within the implied information and knowledge, can help enterprises to establish customer management decisions related to customer relationship management. The data mining method in advanced application in network game, to divide the customer category according to customer attributes, and then establish a customer then according to the customer service system, category, online game operators can be differentiated management. This paper applies self-organizing neural network technology for automatic classification of online game customer, customer relationship management and the classification, the self-organizing map neural network clustering algorithm design. Through the study of this topic the concept of customer relationship management, data mining is introduced based on online game companies, and establish a customer relationship management system for online game companies. The system The functions of customer management, customer basic information management, customer classification, statistical analysis and printing can be completed. The overall design, data flow diagram and the design of each sub module are analyzed in detail, and the detailed design and implementation process is given.
To test the network game customer relationship management system design, test results show that this system not only can be classified according to the customer's difference, but also can be analyzed by the potential customers to be discovered. This system can improve the retention rate of customers, and can excavate the potential customers market potential, improve enterprise game the profits and market competitiveness.

【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：TP311.52

【参考文献】