Research on One-to-One Marketing through Ubiquitous Network

随着互联网作为一种社会基础设施的重要性日益增加，来自互联网的数据挖掘也变得越来越重要。在本研究中，我们探讨了以下数据挖掘技术，以实现网络社会的新营销工具：●提出了一种创造观众对电视剧的关注程度的观众侧注的方法。网络公告栏上充斥着大量观众关于电视节目的对话。我们的方法是提取嵌入在这些对话中的观众的注意力，并以称为“注意力图”的图形结构的形式表达它们。测试结果表明，注意图在指出观看者关注的场景和阐明观看者对场景的印象程度方面，充分发挥了观看者侧面注释的作用。虽然还需要进一步的研究，但这一结果是实现网络营销的重要技术。提出了一种查找垃圾邮件的方法。大量未经请求的电子邮件，通常被称为垃圾邮件，最近急剧增加，不仅对互联网而且对社会构成严重威胁。提出了一种利用文档空间密度信息的垃圾邮件检测方法。虽然提出的方法需要大量的电子邮件流量来获取必要的信息，但在实际条件下，它可以实现完美的检测（即召回率和精确率都是100%）。直接映射的缓存方法有助于每秒处理超过13,000个电子邮件消息。该研究还报告了使用超过5000万个实际电子邮件消息进行的实验结果。●网络安全是维护互联网作为重要社会基础设施的重要问题。特别是，发现P2P海量流量对网络带宽的过度消耗是非常重要的。查找网络病毒也是一个重要的安全问题。虽然流挖掘技术似乎是发现P2P和互联网病毒的有前途的技术，但巨大的网络流量阻碍了这种技术的简单应用。需要一种能够在极其有限的内存下很好地工作的挖掘技术。它还应该具有实时分析能力。在本文中，我们提出了一种基于缓存的挖掘方法来实现这种技术。通过对真实互联网骨干流数据的特征分析，证明了该方法在实现实时分析能力的同时，节省了内存消耗。我们还证明了我们可以使用该方法从互联网主干流量数据中找到质量流量信息。少

Data mining from Internet increases its importance as the Internet increases its importance as a social infrastructure. In this study, we investigate following data mining techniques to realize new marketing tools for the networked society :●A method for creating the viewers' side annotations that reflect viewers' attentions on TV drama are proposed. Internet bulletin boards are filled with large amount of viewers' dialogs concerning TV programs. Our approach is to extract the viewers' attentions embedded in these dialogs and express them in the form of the graphical structure called "attention graph". The testing results demonstrate that attention graphs sufficiently act as viewers' side annotations, in terms of pointing out which scene the viewers pay attentions to and clarifying how deeply viewers' are impressed by the scene. Although further researches are required, this result is an important technique to realize internet marketing.●A method for finding spam mails is proposed. The … More volume of mass unsolicited electronic mail, often known as spam, has recently increased enormously and has become a serious threat not only to the Internet but also to society. We propose a new spam detection method which uses document space density information. Although the proposed method requires extensive e-mail traffic to acquire the necessary information, it can achieve perfect detection (i.e., both recall and precision is 100%) under practical conditions. A direct-mapped cache method contributes to the handling of over 13,000 e-mail messages per second. Experimental results, which were conducted using over 50 million actual e-mail messages, are also reported in this research.●Network security is an important issue in maintaining the Internet as an important social infrastructure. Especially, finding excessive consumption of network bandwidth caused by P2P mass flow is important. Finding Internet viruses are also an important security issue. Although stream mining techniques seem to be promising techniques to find P2P and Internet viruses, vast network flow prevents the simple application of such techniques. A mining technique which works well with extremely limited memory is required. Also it should have a real-time analysis capability. In this paper, we propose a cache based mining method to realize such a technique. By analyzing the characteristics of the proposed method with real Internet backbone flow data, we show the advantages of the proposed method, i.e. less memory consumption while realizing real-time analysis capability. We also show the fact that we can use the proposed method to find mass flow information from Internet backbone flow data. Less