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Research on One-to-One Marketing through Ubiquitous Network

泛在网络一对一营销研究

基本信息

批准号：
15500030
负责人：
YOSHIDA Kenichi
金额：
$ 2.24万
依托单位：
University of TSUKUBA
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2005
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15500030/
关键词：
Data Mining SPAM Internet LRU スパム対策メモリ管理 WWW Graph Based Induction Direct Mapped Cache マスメイルマーケッティングユビキタスネットワーク次世代ネットワーク

项目摘要

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

随着互联网作为社会基础设施的重要性的增加，从互联网中进行数据挖掘的重要性也在增加。在这项研究中，我们研究了以下数据挖掘技术，以实现新的营销工具，为网络社会：●提出了一种方法，用于创建观众侧注释，反映观众对电视剧的关注。互联网上的公告栏充斥着大量的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，注意力图能够很好地作为观众的侧面标注，指出观众关注的是哪个场景，以及观众对该场景的印象有多深。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。●提出了一种发现垃圾邮件的方法。的 ...更多信息通常被称为垃圾邮件的大量未经请求的电子邮件的数量最近急剧增加，并且不仅对因特网而且对社会都已成为严重威胁。我们提出了一种新的利用文档空间密度信息的垃圾邮件检测方法。虽然所提出的方法需要大量的电子邮件业务来获取必要的信息，但它可以实现完美的检测（即，查全率和查准率均为100%。直接映射缓存方法有助于每秒处理超过13，000封电子邮件。本研究还报告了使用超过5000万封实际电子邮件进行的实验结果。●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海量流量导致的网络带宽过度消耗是重要的。查找互联网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Internet病毒的有前途的技术，但庞大的网络流量阻碍了此类技术的简单应用。需要一种在内存极其有限的情况下工作良好的挖掘技术。它还应该具有实时分析能力。在本文中，我们提出了一个基于缓存的挖掘方法来实现这样的技术。通过对真实的Internet骨干流量数据的分析，说明了该方法在实现实时分析能力的同时，具有占用内存少的优点。我们还表明，我们可以使用所提出的方法来找到大量的流量信息，从互联网骨干流数据。少