MoCA+: incorporating user modeling into mobile contextual advertising: demo

Abstract

In-app advertising has become a significant source of revenue for mobile apps. Mobile contextual advertising is one of the recent approaches to improve the effectiveness of in-app 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.