A Proposal of Latent Interest Analysis by Geo-tagged SNS for Advertisement Recommendation
Takanobu Omura, Yukiko Kawai, Shinsuke Nakajima, Kenta T. Suzuki, Yukiko Kawai, Shinsuke Nakajima · 2020
advertisement (ad) recommendation services for mobile users is rapidly increasing. The conventional ways of recommending ads are based on the analysis of users' explicit behavior such as search keywords and keyword matching based on browsing history. However, it might not be effective enough for latent buyers. We have been working on an analysis of the user's latent interest on web browsing history which categorized positive and negative behaviors. In this paper, we adapt the method of the linked pages to real world locations using geo-tagged tweets. By several evaluations, we discuss the possibility to recommend ads according to the user's current location.