MOCA: A novel privacy-preserving contextual advertising platform on mobile devices

Jung Hyun Lee; Woo Jong Ryu; Kang Min Kim; Sang Keun Lee

doi:10.1145/3297280.3297399

MOCA: A novel privacy-preserving contextual advertising platform on mobile devices

Jung Hyun Lee, Woo Jong Ryu, Kang Min Kim, Sang Keun Lee

Korea University

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

1 Scopus citations

Abstract

In this work, we propose a novel contextual advertising platform, called MoCA, which is designed to improve the relevance of in-app advertising in a stand-alone, privacy-protecting manner on mobile devices. MoCA understands the semantics of the current app page and matches semantically relevant ads inside mobile devices. In addition, MoCA controls the degree of privacy protection per user by utilizing a novel semantic generalization model on top of topical taxonomy. Our experimental results verify the effectiveness and feasibility of MoCA with minimal system overheads in terms of runtime, memory usage, and energy consumption.. To the best of our knowledge, this is one of few work on the mobile contextual advertising platform without resort to ad servers.

Original language	English
Title of host publication	Proceedings of the ACM Symposium on Applied Computing
Publisher	Association for Computing Machinery
Pages	1208-1215
Number of pages	8
ISBN (Print)	9781450359337
DOIs	https://doi.org/10.1145/3297280.3297399
State	Published - 2019
Event	34th Annual ACM Symposium on Applied Computing, SAC 2019 - Limassol, Cyprus Duration: 8 Apr 2019 → 12 Apr 2019

Publication series

Name	Proceedings of the ACM Symposium on Applied Computing
Volume	Part F147772

Conference

Conference	34th Annual ACM Symposium on Applied Computing, SAC 2019
Country/Territory	Cyprus
City	Limassol
Period	8/04/19 → 12/04/19

Bibliographical note

Publisher Copyright:
© 2019 Association for Computing Machinery.

Keywords

In-App Advertising
Mobile Contextual Advertising
Semantic Approach

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1145/3297280.3297399

Cite this

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title = "MOCA: A novel privacy-preserving contextual advertising platform on mobile devices",

abstract = "In this work, we propose a novel contextual advertising platform, called MoCA, which is designed to improve the relevance of in-app advertising in a stand-alone, privacy-protecting manner on mobile devices. MoCA understands the semantics of the current app page and matches semantically relevant ads inside mobile devices. In addition, MoCA controls the degree of privacy protection per user by utilizing a novel semantic generalization model on top of topical taxonomy. Our experimental results verify the effectiveness and feasibility of MoCA with minimal system overheads in terms of runtime, memory usage, and energy consumption.. To the best of our knowledge, this is one of few work on the mobile contextual advertising platform without resort to ad servers.",

keywords = "In-App Advertising, Mobile Contextual Advertising, Semantic Approach",

author = "Lee, {Jung Hyun} and Ryu, {Woo Jong} and Kim, {Kang Min} and Lee, {Sang Keun}",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 34th Annual ACM Symposium on Applied Computing, SAC 2019 ; Conference date: 08-04-2019 Through 12-04-2019",

year = "2019",

doi = "10.1145/3297280.3297399",

language = "English",

isbn = "9781450359337",

series = "Proceedings of the ACM Symposium on Applied Computing",

publisher = "Association for Computing Machinery",

pages = "1208--1215",

booktitle = "Proceedings of the ACM Symposium on Applied Computing",

}

Lee, JH, Ryu, WJ, Kim, KM & Lee, SK 2019, MOCA: A novel privacy-preserving contextual advertising platform on mobile devices. in Proceedings of the ACM Symposium on Applied Computing. Proceedings of the ACM Symposium on Applied Computing, vol. Part F147772, Association for Computing Machinery, pp. 1208-1215, 34th Annual ACM Symposium on Applied Computing, SAC 2019, Limassol, Cyprus, 8/04/19. https://doi.org/10.1145/3297280.3297399

MOCA: A novel privacy-preserving contextual advertising platform on mobile devices. / Lee, Jung Hyun; Ryu, Woo Jong; Kim, Kang Min et al.
Proceedings of the ACM Symposium on Applied Computing. Association for Computing Machinery, 2019. p. 1208-1215 (Proceedings of the ACM Symposium on Applied Computing; Vol. Part F147772).

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

TY - GEN

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AB - In this work, we propose a novel contextual advertising platform, called MoCA, which is designed to improve the relevance of in-app advertising in a stand-alone, privacy-protecting manner on mobile devices. MoCA understands the semantics of the current app page and matches semantically relevant ads inside mobile devices. In addition, MoCA controls the degree of privacy protection per user by utilizing a novel semantic generalization model on top of topical taxonomy. Our experimental results verify the effectiveness and feasibility of MoCA with minimal system overheads in terms of runtime, memory usage, and energy consumption.. To the best of our knowledge, this is one of few work on the mobile contextual advertising platform without resort to ad servers.

KW - In-App Advertising

KW - Mobile Contextual Advertising

KW - Semantic Approach

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M3 - Conference contribution

AN - SCOPUS:85065648257

SN - 9781450359337

T3 - Proceedings of the ACM Symposium on Applied Computing

SP - 1208

EP - 1215

BT - Proceedings of the ACM Symposium on Applied Computing

PB - Association for Computing Machinery

Y2 - 8 April 2019 through 12 April 2019

ER -

MOCA: A novel privacy-preserving contextual advertising platform on mobile devices

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

Access to Document

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Cite this