基于D-S证据理论对超市消费者购物分析

介绍了D-S证据理论的基本原理,结合超市消费者需求情况,给出了一个利用D-S证据理论来对消费者购买商品不确定性的确定性计算算法。     

IP电话业务系统与多层分布式体系技术

随着IP增值业务的不断发展以及Internet的发展普及,新的分布式应用系统产生了,它将业务处理与客户交互分开来,实现了瘦客户/业务服务/数据服务的多层分布式体系结构。文中对以中间件为基础框架的多层分布式体系技术进行了介绍,分析了多层分布式体系技术在电信IP电话业务中的应用,给出了相关体系流程和MQ消息中间件的多层分布式体系事例。     

企业虚拟形态下的质量保证体系

对比分析了虚拟企业与传统企业的不同,基于虚拟企业独有的特点,建立了虚拟企业质量保证体系模型——铁三角模型．阐述了信息质量管理体系、客户服务质量管理体系、供应链质量管理体系以及各成员企业传统ISO9000质量管理体系在虚拟企业这一环境下的含义、特点和作用．     

CRM中基于RBAC的改进模型的研究与设计

角色访问控制(role-based access control,RBAC)技术在信息安全领域日渐成熟,但在处理角色的势约束问题方面还有待进一步研究.为了解决这一问题,在此,提出了一种树状细粒度RBAC模型(treelike and little granularity-oriented RBAC,tgRBAC),该模型是从RBAC模型演化而来的.并进一步给出了基于J2EE架构的该模型的实现模型,对解决企业中普遍存在的垂直领导时角色具有势约束问题进行了研究.并在某集团客户关系管理系统(XJ_CRM)中进行了具体的实践.     

基于C#的远程数据库访问系统的设计和实现

该系统应用微软公司新开发的语言C#,以网络编程核心WindowsSockets和客户/服务器模式为基础,实现对远程数据库的访问。服务器与数据库服务器通过ActiveX数据对象(ADO.NET)中的数据提供程序SQLServer.NET来连接,服务器负责把客户端命令解释为SQLServer语句,然后提交给数据库服务器进行操作,并把返还结果传给客户端。客户对信息的获取快捷方便。ADO.NET使得对系统的维护和更改更容易,系统的可伸缩性与互操作性更强。该系统可以运用在企业的网络数据库系统中。     

电脑客户服务中心知识库系统研究

设计了一种电脑故障维修知识库系统，用产生式规则表示知识，用关系数据库构建知识库及知识库管理系统，采用启发式搜索策略和正向推理机制，使客服人员与客户可以快速地检索到所需要的资料，为电脑故障排除提供指导，从而提高客户服务工作效率和客户满意度。     

基于信息熵的蚁群聚类算法在客户细分中的应用①

传统的蚁群聚类算法需设置较多参数,且聚类时间较长。基于信息熵的蚁群聚类算法通过信息熵改变蚂蚁拾起和放下数据的规则,减少了参数的设置、缩短了聚类的时间,将其应用于客户细分,并且与采用传统的蚁群聚类算法得到的细分结果进行比较分析,实验表明。基于信息熵的蚁群聚类算法可以加快客户细分的聚类进程。     

再多一次接触:顾客反馈机制对服务失败后顾客评价的影响

It is difficult to control service quality for any service firm and service failure is inevitable due to human or non-human factors. As a result, service recovery stirred the interest of researchers and practitioners. However, service failure may not be identified by firms because a majority of dissatisfied customers will not complain to the service provider. Thus, this research proposes a proactive customer feedback mechanism comprised of proactive solicitation of customer feedback, customers providing feedback and follow-up communication and examine their impact of customer evaluations in the context of service failure. This research tries to establish that through adding a continuous series of satisfied service encounters or "moment of truth" to service failure encounters, the customer evaluations (e.g. satisfaction, trust, purchase intent and positive WOM) toward the service will be significantly improved. Our research employed a 2×2×2 between subjects experimental design. Three independent variables were manipulated as presence and absence level, that is, firms either proactively solicitted customer feedback or employed no solicitation of feedback, Customers either provided feedback to the service firm or refused to provide feedback, and service firm either conducted follow-up communication or no follow-up communication. Our research adoptted a scenario in the context of patronizing a three-star hotel on a business trip. In total, 221 business administration graduates from a famous university in Shanghai participated in the experiment. MANOVA was used to test the hypotheses. The results indicated that proactive solicitation significantly influenced trust (p<0.01). Besides satisfaction, the other dependent variables such as trust, purchase intent and positive WOM significantly differred between with and without follow-up communication groups (p<0.05). Third, a significant difference was detected regarding satisfaction, trust, purchase intent and positive WOM between customer providing feedback groups and no customer feedback groups (p<0.05). Moreover, significant interactive effects were found of customers provided feedback and follow-up communication on trust and purchase intent. Trust and purchase intent reached highest when a follow-up communication occurred after customers provided feedback. However, no interactive effects were found of proactive solicitation of customer feedback and customer providing feedback. This research suggests that service providers should create new encounters with customers when they are confronted with service failure, and in this study, through proactive customer feedback mechanism. That is, first, the service provider should encourage customers to provide feedback, which can improve customer evaluations after service failure and after customers providing feedback. At the same time, the firm should employ follow-up communication with the customer and inform them about how the firm responded to their complaints, suggestions and comments. It is worth to note that companies just need to have follow-up communication with those customers who have provided feedback. More important, as information technology and internet prevails, it is very likely sending email and short messages after a service failure to maintain customer relationships could significantly enhance customer evaluations of the service provider. Of course, how consumers respond to such measures online is an promising research area and needs further investigation.     

一种CPS中C#与C++代码互访方法的研究

客户编程软件(CPS)是对讲机等无线通讯系统Radio配置系统的核心技术,实现C#与C 代码的互访是CPS设计的研究热点之一。提出了一种利用平台调用和回调函数的形式实现C#与C 的互访的方法。该方法既保持C#语言进行软件开发具有开发效率高、便于维护和管理的优势,又具有C 开发的系统执行效率高和健壮性高的特点,并且提供了对系统底层更灵活的访问的能力,该方法是一种Radio配置系统CPS的好方法。     

E-Commerce Recommendation Applications

Recommender systems are being used by an ever-increasing number of E-commerce sites to help consumers find products to purchase. What started as a novelty has turned into a serious business tool. Recommender systems use product knowledge—either hand-coded knowledge provided by experts or mined knowledge learned from the behavior of consumers—to guide consumers through the often-overwhelming task of locating products they will like. In this article we present an explanation of how recommender systems are related to some traditional database analysis techniques. We examine how recommender systems help E-commerce sites increase sales and analyze the recommender systems at six market-leading sites. Based on these examples, we create a taxonomy of recommender systems, including the inputs required from the consumers, the additional knowledge required from the database, the ways the recommendations are presented to consumers, the technologies used to create the recommendations, and the level of personalization of the recommendations. We identify five commonly used E-commerce recommender application models, describe several open research problems in the field of recommender systems, and examine privacy implications of recommender systems technology.