在线广告网络的评估与优化
发布时间：2018-10-31 17:10
【摘要】：在线广告如今已经成为一个拥有200亿美元的产业。它在成为众多网站提供商和一些广告中介商的重要收益来源的同时,也为广告商提供了新的媒体平台。为了使得广告中介商更有效地为终端用户提供在线广告,从而增加广告的点击量;我们必须首先了解广告中介商网络在网络层面与内容层面运行情况的不足,然后再进一步地进行改进。本论文首先测量了现有的三个主流在线广告网络平台:Google、AOL/Akamai和Adblade,并量化了他们网络层面和内容层面的性能。在此基础上,本论文从基于用户地理位置和基于用户行为的在线广告投放机制这两个方面来改进现有的在线广告网络。本论文的主要创新性成果包括以下四个方面: 1.本论文是学术领域中第一篇从网络层面和内容层面测量在线广告网络的文章。本论文设计并实现了一套从网络层面和内容层面审计在线广告网络的系统。该系统可以广泛运用于任一广告中介商网络中,有效地监控并帮助调控基于Web的广告业。通过使用这个系统,本论文对拥有不同设计理念的广告中介商在网络层面和内容层面进行了分析,并证明了在线广告网络的底层设计与上层的网络层面和内容层面的服务有很大的关系。 2.本论文设计并实现了一套精确度逐步提高的、无需客户端支持的IP地址位置定位系统。该系统把Web的数据挖掘和Internet网络测量的定位方法有效结合在一起,从而避免了单独使用任何一种方法所带来的不精确因素。通过对学校IP数据集上的测试,本论文证实这套系统的中值误差距离仅为690米。这比之前最好的IP地理定位系统的准确度提高了50倍。因此,当这套系统嵌入到基于用户地理位置的在线广告网络中,它可以很大程度上改进在线广告投放的有效性。 3.本论文设计并实现了一套不需分析用户数据包有效载荷,可高准确度地恢复用户网页浏览记录的系统。该系统把Web网站爬寻统计和Internet网络流量分析方法有效结合,而不使用违反互联网法律的深度包检测技术。通过恢复大规模级别的网络流中的用户浏览记录,本论文证实这套系统可以达到86%以上的恢复成功率,和5%以下的误报率。因此,当这套系统嵌入到基于用户行为的在线广告网络中,它可以从根本上改变在线广告投放的合法性。 4.本论文设计并实现了一套根据用户的浏览模式来准确自动地标识用户在线兴趣的系统。对于每一项用户浏览记录,该系统通过网站的域名或者在搜索引擎返回的结果上,采用关键字匹配的方法来实现兴趣分类。通过对三个月包含4.5万个用户的DNS网络流进行实验,本论文证实该套系统的正确率可以86.44%。因此,当这套系统嵌入到基于用户行为的在线广告网络中,它可以很大程度上改进在线广告投放的有效性。
[Abstract]:Online advertising has become an industry of $20 billion. It not only becomes an important source of revenue for many website providers and some advertising agencies, but also provides a new media platform for advertisers. In order to make the advertising agency more effective to provide online advertising to end users, thus increasing the number of ads click; We must first understand the shortcomings of the advertising intermediary network at the network level and the content level, and then further improve it. In this paper, we first measure the three main online advertising network platforms: Google,AOL/Akamai and Adblade, and quantify their performance at the network level and content level. On this basis, this paper improves the existing online advertising network from two aspects: user geographical location and online advertising mechanism based on user behavior. The main innovative achievements of this paper include the following four aspects: 1. This paper is the first in the academic field to measure the online advertising network at the network level and content level. This paper designs and implements a set of online advertising network audit system from the network level and content level. The system can be widely used in any advertising agency network and can effectively monitor and control the advertising industry based on Web. Through the use of this system, this paper analyzes the advertising agencies with different design concepts at the network level and content level. It is proved that the bottom layer design of online advertising network is closely related to the service at the network and content level. 2. In this paper, we design and implement a IP address location system with improved precision and no client support. The system combines the data mining of Web and the positioning method of Internet network measurement effectively, thus avoiding the imprecise factors brought by using any method alone. The median error distance of this system is only 690m by testing the school IP data set. This is 50 times more accurate than the previous best IP geographic positioning system. Therefore, when the system is embedded in the online advertising network based on users' geographical location, it can greatly improve the effectiveness of online advertising. 3. In this paper, we design and implement a system that can recover the user's browsing record accurately without analyzing the payload of the user's packet. This system combines Web website crawling statistics with Internet network traffic analysis method effectively, and does not use the depth packet detection technology which violates the Internet law. By restoring user browsing records in large-scale network flows, this paper confirms that the system can achieve a recovery success rate of more than 86% and false alarm rate of less than 5%. Therefore, when the system is embedded in the online advertising network based on user behavior, it can fundamentally change the legitimacy of online advertising. 4. In this paper, we design and implement a system to identify the online interest of users accurately and automatically according to the user's browsing mode. For each user browsing record, the system uses keyword matching method to realize interest classification through the domain name of the website or the result returned by the search engine. Through the experiments on the DNS network flow with 45000 users in three months, this paper proves that the correct rate of the system can be 86.44. Therefore, when the system is embedded in the online advertising network based on user behavior, it can greatly improve the effectiveness of online advertising.
【学位授予单位】：电子科技大学
【学位级别】：博士
【学位授予年份】：2011
【分类号】：TP393.092
本文编号：2302992
[Abstract]:Online advertising has become an industry of $20 billion. It not only becomes an important source of revenue for many website providers and some advertising agencies, but also provides a new media platform for advertisers. In order to make the advertising agency more effective to provide online advertising to end users, thus increasing the number of ads click; We must first understand the shortcomings of the advertising intermediary network at the network level and the content level, and then further improve it. In this paper, we first measure the three main online advertising network platforms: Google,AOL/Akamai and Adblade, and quantify their performance at the network level and content level. On this basis, this paper improves the existing online advertising network from two aspects: user geographical location and online advertising mechanism based on user behavior. The main innovative achievements of this paper include the following four aspects: 1. This paper is the first in the academic field to measure the online advertising network at the network level and content level. This paper designs and implements a set of online advertising network audit system from the network level and content level. The system can be widely used in any advertising agency network and can effectively monitor and control the advertising industry based on Web. Through the use of this system, this paper analyzes the advertising agencies with different design concepts at the network level and content level. It is proved that the bottom layer design of online advertising network is closely related to the service at the network and content level. 2. In this paper, we design and implement a IP address location system with improved precision and no client support. The system combines the data mining of Web and the positioning method of Internet network measurement effectively, thus avoiding the imprecise factors brought by using any method alone. The median error distance of this system is only 690m by testing the school IP data set. This is 50 times more accurate than the previous best IP geographic positioning system. Therefore, when the system is embedded in the online advertising network based on users' geographical location, it can greatly improve the effectiveness of online advertising. 3. In this paper, we design and implement a system that can recover the user's browsing record accurately without analyzing the payload of the user's packet. This system combines Web website crawling statistics with Internet network traffic analysis method effectively, and does not use the depth packet detection technology which violates the Internet law. By restoring user browsing records in large-scale network flows, this paper confirms that the system can achieve a recovery success rate of more than 86% and false alarm rate of less than 5%. Therefore, when the system is embedded in the online advertising network based on user behavior, it can fundamentally change the legitimacy of online advertising. 4. In this paper, we design and implement a system to identify the online interest of users accurately and automatically according to the user's browsing mode. For each user browsing record, the system uses keyword matching method to realize interest classification through the domain name of the website or the result returned by the search engine. Through the experiments on the DNS network flow with 45000 users in three months, this paper proves that the correct rate of the system can be 86.44. Therefore, when the system is embedded in the online advertising network based on user behavior, it can greatly improve the effectiveness of online advertising.
【学位授予单位】：电子科技大学
【学位级别】：博士
【学位授予年份】：2011
【分类号】：TP393.092
【共引文献】
相关硕士学位论文 前1条
1 姚园园;Internet拓扑结构研究及在IM网络建模中的应用[D];郑州大学;2006年
，本文编号：2302992
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