Unintrusive customization techniques for Web advertising

Langheinrich, Marc; Nakamura, Atsuyoshi; Abe, Naoki; Kamba, Tomonari; Koseki, Yoshiyuki

doi:10.1016/s1389-1286(99)00033-x

Cited by 97 publications

(64 citation statements)

References 9 publications

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“…The system Adnostic by Toubiana et al [17] uses a browser extension that incorporates behavioral targeting algorithm based on a local database of browsing history, not shared with external parties. Similar attempts towards privacy protecting techniques have been explored by Langheririch et al [8] and Tomlin [16]. In 2011, Riderer et al [14] proposed an alternative mechanism of transitional privacy, allowing the user to decide what personal information is released and put on sale while receiving compensation for it.…”

Section: B Behavioral Tracking and Responsesmentioning

confidence: 96%

Network Analysis of Third Party Tracking: User Exposure to Tracking Cookies through Search

Gomer

Rodrigues

Milić-Frayling

et al. 2013

2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)

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Abstract-Internet advertisers reach millions of customers through practices that real time tracking of users' online activities. The tracking is conducted by third party ad services engaged by the Web sites to facilitate marketing campaigns. Previous research has investigated tracking practices and tracking agencies associated with popular Web sites. Here we investigate the network properties of the third party referral structures that facilitate gathering of user information for the delivery of personalized ads. By considering third party domains associated with the top ten search results for a diverse set of queries, we arrived at the networks of third party domains in four search markets. We show a consistent network structure across markets, with a dominant connected component that, on average, includes 92.8% of network vertices and 99.8% of the connecting edges. There is 99.5% chance that a user will become tracked by all top 10 trackers within 30 clicks on search results. Finally, the third party networks exhibit properties of the small world networks. This implies a high-level global and local efficiency in spreading the user information and delivering targeted ads.

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Section: B Behavioral Tracking and Responsesmentioning

confidence: 96%

Network Analysis of Third Party Tracking: User Exposure to Tracking Cookies through Search

Gomer

Rodrigues

Milić-Frayling

et al. 2013

2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)

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“…For example, in a 4-level pricing scheme, say, the advertiser pays 5¢ for exposures to viewers with compatibility scores in the interval [0.3, 0.7); 8¢ for the interval [0.7, 0.9) and 13¢ for [0. 9,1]. In this example the advertiser doesn't pay for viewers that have compatibility score less than 0.3.…”

Section: Co-published By Atlantis Press and Taylor And Francismentioning

confidence: 99%

“…ADWIZ system classifies the users according to the keywords they posted at the website and assigns the advertisements using linear programming approach 9 . The model includes two constraints, namely, the minimum number of exposures associated with the advertisements and the coverage constraint that guarantees that certain portion of the users with specific features are exposed to a particular advertisement.…”

Section: Relevant Literaturementioning

confidence: 99%

Computational Intelligence Based Decision Support Tool for Personalized Advertisement Assignment System

Kılıç¹,

Bozkurt²

2013

IJCIS

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In this paper a comprehensive framework that maximizes advertising revenues of a company in a personalized advertisement setting is presented. The research was motivated from a real life problem faced by a company that develops a web based 3-D virtual reality social platform. The objective of the research was both development of a novel business model and the framework. Four heuristics are proposed as part of the framework. The performance of these heuristics was tested with an experimental analysis.

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“…It operates by receiving HTTP request and sending appropriate file to client terminal [8]. Ad server can provide many additional functions, e.g.…”

Section: Adservermentioning

confidence: 99%

Prototype of High Performance Scalable Advertising Server with Local Memory Storage and Centralised Processing

Marszałkowski¹

2012

Information and Communication Technologies

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Abstract. Advertising servers play an important role in the entire contrary e-business. In this paper an approach for a high performance ad server is proposed. A prototype of a new architecture is presented: system achieving scalability by multiplication of ad servers with separate local memory storage and single managing server for entire cluster of those, providing data processing and ads preparation.The paper includes benchmarks of alternate technologies possible at the design stage, results of the stress tests of the prototype, as well as the data from its performance with real web traffic. Limitations of the proposed solution are discussed. Although the prototype is created on a specific platform, all technologies used are widely available or have replacements on other platforms, granting generality to the proposed solution.

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Unintrusive customization techniques for Web advertising

Cited by 97 publications

References 9 publications

Network Analysis of Third Party Tracking: User Exposure to Tracking Cookies through Search

Network Analysis of Third Party Tracking: User Exposure to Tracking Cookies through Search

Computational Intelligence Based Decision Support Tool for Personalized Advertisement Assignment System

Prototype of High Performance Scalable Advertising Server with Local Memory Storage and Centralised Processing

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