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 |
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Pages | 1208-1215 |
Number of pages | 8 |
DOIs | |
Publication status | Published - 2019 Jan 1 |
Event | 34th Annual ACM Symposium on Applied Computing, SAC 2019 - Limassol, Cyprus Duration: 2019 Apr 8 → 2019 Apr 12 |
Conference
Conference | 34th Annual ACM Symposium on Applied Computing, SAC 2019 |
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Country/Territory | Cyprus |
City | Limassol |
Period | 19/4/8 → 19/4/12 |
Keywords
- In-App Advertising
- Mobile Contextual Advertising
- Semantic Approach
ASJC Scopus subject areas
- Software