Demo: MoCA+: Incorporating user modeling into mobile contextual advertising

So Jung Park, Jung Hyun Lee, So Young Jun, Kang Min Kim, Sang-Geun Lee

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    1 Citation (Scopus)

    Abstract

    In-app advertising has become a signifcant source of revenue for mobile apps. Mobile contextual advertising is one of the recent approaches to improve the effectiveness of inapp advertising, which seeks to target an app page content that a user is viewing. Typically, mobile contextual advertising is based on the cloud-based architecture, which may cause many privacy concerns, because in-device user data inevitably sends to ad servers. In our previous work [3], we developed a novel mobile contextual advertising platform, called MoCA, which was designed to improve the relevance of in-app ads in a privacy protecting manner. However, MoCA does not explicitly model user interests. In this demo, we present yet another mobile contextual advertising platform, called MoCA+, which incorporates user modeling into MoCA. It is designed to provide contextual in-app ads to third-party apps through its well-defned APIs. MoCA+ collects a variety of user data inside a mobile device to model user interests. It then matches contextual ads considering both the user interests and an app page content based on the semantic technique [2]. Since the proposed platform explicitly targets user interests, it is expected to satisfy the user's information needs, resulting in a better user experience on in-app advertising. As opposed to typical mobile contextual advertising that is based on big data analytics on ad servers, MoCA+ performs all the key essential tasks locally. It, therefore, protects user privacy without sending out any in-device data. To the best of our knowledge, this is one of few works to implement the mobile contextual advertising platform without resort to servers.

    Original languageEnglish
    Title of host publicationMiddleware 2017 - Proceedings of the 2017 Middleware Posters and Demos 2017
    Subtitle of host publicationProceedings of the Posters and Demos Session of the 18th International Middleware Conference
    PublisherAssociation for Computing Machinery, Inc
    Pages21-22
    Number of pages2
    ISBN (Electronic)9781450352017
    DOIs
    Publication statusPublished - 2017 Dec 11
    Event18th ACM/IFIP/USENIX International Middleware Conference, Middleware 2017 - Las Vegas, United States
    Duration: 2017 Dec 112017 Dec 15

    Publication series

    NameMiddleware 2017 - Proceedings of the 2017 Middleware Posters and Demos 2017: Proceedings of the Posters and Demos Session of the 18th International Middleware Conference

    Other

    Other18th ACM/IFIP/USENIX International Middleware Conference, Middleware 2017
    Country/TerritoryUnited States
    CityLas Vegas
    Period17/12/1117/12/15

    Bibliographical note

    Funding Information:
    This work was supported in part by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (No. 2015R1A2A1A10052665 and 2015R1A2A1A15052701). This work was also in part supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITP (Institute for Information communications Technology Promotion) (No. IITP-2017-2016-0-00464-002).

    Publisher Copyright:
    © 2017 held by the owner/author(s).

    ASJC Scopus subject areas

    • Software
    • Information Systems

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