Revenue-Optimized Webpage Recommendation

Chong Wang; Achir Kalra; Cristian Borcea; Yi Chen

doi:10.1109/ICDMW.2015.215

Revenue-Optimized Webpage Recommendation

Chong Wang, Achir Kalra, Cristian Borcea, Yi Chen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

3 Scopus citations

Abstract

As a massive industry, display advertising delivers advertisers' marketing messages to attract customers throughbanners shown on webpages. For publishers, i.e. websites, display advertising is the most critical revenue source. Most existing webpage recommender systems suggest webpages based on user interests only. However, the articles of interest to specific users may not be profitable to publishers. Conversely, only recommending the most profitable articles may lose publishers' user base. To address this issue, we will conduct a series of investigations anddesign Revenue-Optimized Recommendation, aims to recommend users webpages that optimize interestingness and ad revenue.

Original language	English (US)
Title of host publication	Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Editors	Xindong Wu, Alexander Tuzhilin, Hui Xiong, Jennifer G. Dy, Charu Aggarwal, Zhi-Hua Zhou, Peng Cui
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1558-1559
Number of pages	2
ISBN (Electronic)	9781467384926
DOIs	https://doi.org/10.1109/ICDMW.2015.215
State	Published - Jan 29 2016
Event	15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 - Atlantic City, United States Duration: Nov 14 2015 → Nov 17 2015

Publication series

Name	Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Other

Other	15th IEEE International Conference on Data Mining Workshop, ICDMW 2015
Country/Territory	United States
City	Atlantic City
Period	11/14/15 → 11/17/15

All Science Journal Classification (ASJC) codes

Electrical and Electronic Engineering
Computer Science Applications

Keywords

Computational Advertising
Recommender System

Access to Document

10.1109/ICDMW.2015.215

Cite this

Wang, C., Kalra, A., Borcea, C., & Chen, Y. (2016). Revenue-Optimized Webpage Recommendation. In X. Wu, A. Tuzhilin, H. Xiong, J. G. Dy, C. Aggarwal, Z.-H. Zhou, & P. Cui (Eds.), Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 (pp. 1558-1559). Article 7395860 (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICDMW.2015.215

Wang, Chong ; Kalra, Achir ; Borcea, Cristian et al. / Revenue-Optimized Webpage Recommendation. Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015. editor / Xindong Wu ; Alexander Tuzhilin ; Hui Xiong ; Jennifer G. Dy ; Charu Aggarwal ; Zhi-Hua Zhou ; Peng Cui. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 1558-1559 (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015).

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title = "Revenue-Optimized Webpage Recommendation",

abstract = "As a massive industry, display advertising delivers advertisers' marketing messages to attract customers throughbanners shown on webpages. For publishers, i.e. websites, display advertising is the most critical revenue source. Most existing webpage recommender systems suggest webpages based on user interests only. However, the articles of interest to specific users may not be profitable to publishers. Conversely, only recommending the most profitable articles may lose publishers' user base. To address this issue, we will conduct a series of investigations anddesign Revenue-Optimized Recommendation, aims to recommend users webpages that optimize interestingness and ad revenue.",

keywords = "Computational Advertising, Recommender System",

author = "Chong Wang and Achir Kalra and Cristian Borcea and Yi Chen",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015 ; Conference date: 14-11-2015 Through 17-11-2015",

year = "2016",

month = jan,

day = "29",

doi = "10.1109/ICDMW.2015.215",

language = "English (US)",

series = "Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1558--1559",

editor = "Xindong Wu and Alexander Tuzhilin and Hui Xiong and Dy, {Jennifer G.} and Charu Aggarwal and Zhi-Hua Zhou and Peng Cui",

booktitle = "Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015",

address = "United States",

}

Wang, C, Kalra, A, Borcea, C & Chen, Y 2016, Revenue-Optimized Webpage Recommendation. in X Wu, A Tuzhilin, H Xiong, JG Dy, C Aggarwal, Z-H Zhou & P Cui (eds), Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015., 7395860, Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015, Institute of Electrical and Electronics Engineers Inc., pp. 1558-1559, 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015, Atlantic City, United States, 11/14/15. https://doi.org/10.1109/ICDMW.2015.215

Revenue-Optimized Webpage Recommendation. / Wang, Chong; Kalra, Achir; Borcea, Cristian et al.
Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015. ed. / Xindong Wu; Alexander Tuzhilin; Hui Xiong; Jennifer G. Dy; Charu Aggarwal; Zhi-Hua Zhou; Peng Cui. Institute of Electrical and Electronics Engineers Inc., 2016. p. 1558-1559 7395860 (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Revenue-Optimized Webpage Recommendation

AU - Wang, Chong

AU - Kalra, Achir

AU - Borcea, Cristian

AU - Chen, Yi

PY - 2016/1/29

Y1 - 2016/1/29

N2 - As a massive industry, display advertising delivers advertisers' marketing messages to attract customers throughbanners shown on webpages. For publishers, i.e. websites, display advertising is the most critical revenue source. Most existing webpage recommender systems suggest webpages based on user interests only. However, the articles of interest to specific users may not be profitable to publishers. Conversely, only recommending the most profitable articles may lose publishers' user base. To address this issue, we will conduct a series of investigations anddesign Revenue-Optimized Recommendation, aims to recommend users webpages that optimize interestingness and ad revenue.

AB - As a massive industry, display advertising delivers advertisers' marketing messages to attract customers throughbanners shown on webpages. For publishers, i.e. websites, display advertising is the most critical revenue source. Most existing webpage recommender systems suggest webpages based on user interests only. However, the articles of interest to specific users may not be profitable to publishers. Conversely, only recommending the most profitable articles may lose publishers' user base. To address this issue, we will conduct a series of investigations anddesign Revenue-Optimized Recommendation, aims to recommend users webpages that optimize interestingness and ad revenue.

KW - Computational Advertising

KW - Recommender System

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M3 - Conference contribution

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T3 - Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

SP - 1558

EP - 1559

BT - Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

A2 - Wu, Xindong

A2 - Tuzhilin, Alexander

A2 - Xiong, Hui

A2 - Dy, Jennifer G.

A2 - Aggarwal, Charu

A2 - Zhou, Zhi-Hua

A2 - Cui, Peng

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015

Y2 - 14 November 2015 through 17 November 2015

ER -

Wang C, Kalra A, Borcea C , Chen Y. Revenue-Optimized Webpage Recommendation. In Wu X, Tuzhilin A, Xiong H, Dy JG, Aggarwal C, Zhou ZH, Cui P, editors, Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 1558-1559. 7395860. (Proceedings - 15th IEEE International Conference on Data Mining Workshop, ICDMW 2015). doi: 10.1109/ICDMW.2015.215

Revenue-Optimized Webpage Recommendation

Abstract

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All Science Journal Classification (ASJC) codes

Keywords

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