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论 文 题 目 基于排队论在线客服系统的优化设计与实现 学 科、专 业 计算机科学与技术 研 究 生 姓 名

导 师

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摘 要

在线客服系统联系着企业与客户，是企业把握市场脉搏，掌握市场动向，了解客户信息的重要工具。企业要做到高效益和高效率的处理客户的要求，就必须优化在线客服系统的工作机制、服务效率，提高企业的服务质量，缩短对客户等待服务的响应周期，提高企业竞争力。

本文首先对在线客服系统的特征和实际数据进行分析，确定可以用排队论对在线客服系统进行建模优化，通过对M/M/n和M/M/1排队方式性能的比较，决定用M/M/n排队方式对在线客服系统进行建模，在此基础上，分别从排队方式、客户容忍度、企业效率和决策策略四个方面对在线客服系统进行了优化设计。接着分别从功能性和非功能性两个方面对在线客服系统的需求进行了分析，然后从排队方式、调度策略、功能结构、体系结构和数据库五个方面对系统分别进行了分析设计，在此基础上，在J2EE规范下实现了优化后的基于排队论在线客服系统，对其性能进行了分析，结果表明，优化后的在线客服系统性能明显优于未优化的客服系统。

关键词：在线客服；排队论；分时策略；优化设计

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Abstract

Enterprise and the customer is linked by online customer service system, it is the tool with which the enterprise to grasp the pulse of the market, grasp market trends, understand customer information important. Companies to achieve high efficiency and high efficiency processing customer requirements, it is necessary to optimize the online customer service system working mechanism, service efficiency, improve the service quality of the enterprise, to reduce customer waiting service response time, improve the competitiveness of enterprises.

On the online customer service system characteristic and the actual data are analysed in this paper, which can be determined by using queuing theory to the online customer service system modeling and optimization, based on the M / M / N and M / M / 1 queue performance comparison, decided to use M / M / N queue on online customer service system modeling, on the basis of on the way, separately from the queue, customer tolerance, enterprise efficiency and decision strategies in four aspects of online customer service system optimized design. And then separately from the functional and non-functional two aspects of online customer service system needs analysis, and then from the queue, scheduling strategy, function structure, system structure and the database of five aspects of the system are analyzed the design, on the basis of this, the J2EE specification achieved under optimized based on queuing theory online customer service system, its performance analysis, the results show that after the optimization, online customer service system performance are significantly superior to the optimization of the customer service system.

Keywords: customer service; queuing theory; Timeshare strategy; Optimization design

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