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AdNext
Author(s) -
Byoungjip Kim,
Jin-Young Ha,
SangJeong Lee,
Seungwoo Kang,
Youngki Lee,
Yunseok Rhee,
Lama Nachman,
Junehwa Song
Publication year - 2011
Publication title -
singapore management university institutional knowledge (ink) (singapore management university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.1145/2184489.2184492
Subject(s) - computer science , key (lock) , probabilistic logic , shopping mall , mobile device , mobile computing , world wide web , multimedia , computer security , artificial intelligence , telecommunications , advertising , business
As smartphones have become prevalent, mobile advertising is getting significant attention as being not only a killer application in future mobile commerce, but also as an important business model of emerging mobile applications to monetize them. In this paper, we present AdNext, a visit-pattern-aware mobile advertising system for urban commercial complexes. AdNext can provide highly relevant ads to users by predicting places that the users will next visit. AdNext predicts the next visit place by learning the sequential visit patterns of commercial complex users in a collective manner. As one of the key enabling techniques for AdNext, we develop a probabilistic prediction model that predicts users' next visit place from their place visit history. To automatically collect the users' place visit history by smartphones, we utilize Wi-Fi-based indoor localization. We demonstrate the feasibility of AdNext by evaluating the accuracy of the prediction model. For the evaluation, we used a dataset collected from COEX Mall, the largest commercial complex in South Korea. Also, we implemented an initial prototype of AdNext with the latest smartphones, and deployed it in COEX Mall.

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