毕业论文--Web病毒式营销核心群体挖掘与全局营销策略优化.doc

摘 要 首先，根据国内先进的Web病毒式营销数据挖掘理论，在同时考虑影响客户购买产品或服务的内在因素与外在因素的基础上，构建了基于客户信任网络的产品信息扩散模型(CTN Based Diffusion of Product Information)，并通过引入环境影响解决了孤立点的接受与推荐问题。 其次，针对静态的CTN网络，设计了两种核心群体挖掘算法——VMCGM(Viral Marketing Core Group Mining)与E-VMCGM(Enhanced VMCGM)，实现了病毒式营销核心群体的挖掘。 第三，由于动态性是社会网络的本质之一，为了实现客户信任网络的动态更新，避免传统的连续型病毒式营销策略带来的重复计算问题，设计并实现了基于网络更新日志(Network Change Log，NCL)的核心群体动态挖掘算法DMCG(Dynamically Mining Core Group)。该算法可在解决上述两个问题的同时，能够保证核心群体挖掘的准确度。 最后，考虑到产品负面评价信息对购买者的影响，设计实现了一种产品负面影响控制算法，实现了一定程度上的负面影响传播的控制。 关键词：病毒式营销；客户信任网络；核心群体挖掘；社会网络；动态挖掘 Abstract With the development of E-commerce, Web viral marketing is being concerned and applied more widely according to its unique advantages compared with traditional ways. At present, data mining has been successfully employed in traditional marketing; however, there is little work on viral marketing. Firstly,the project base on advanced Web-based viral marketing of data mining theory, taking into account both internal factors and external factors when customer purchasing products or services,building CTN based diffusion of product information model.At the same time, by introducing the environmental impact ,acceptance and recommendation problems of isolated node has been resolved. Secondly,the VMCGM and E-VMCGM core group mining algorithms which working on the static CTN based network was introduced to implement the core groups of viral marketing mining. Thirdly,the dynamic character is social networks in itself, in order to achieving the dynamic update of CTN networks and avoiding redundant counting which appears on traditional continuous viral marketing strategy, the project implement a network change log(NCL)based dynamically mining core group algorithm (DMCG). The algorithm can solve the two problems above and to ensure the accuracy of the core group mining meanwhile. Finally, the project implement negative impact control algorithm which take effect to some extent. Keywords: Viral Marketing; Customer Trust Network; Mining Core Gro