[4Xin1] Poster session 2

[4Xin1-48] Building a model for detecting store closures using an in-house competition

〇Nachiko Takeshita¹, Shuji Yamaguchi¹, Naomi Sasaya¹, Kota Tsubouchi¹ (1.Yahoo Japan Corporation)

Keywords:store closures, in-house competition, machine learning

Store closures are often difficult to detect in the database because of their routinely. Then, we conduct an in-house competition to build a model for detecting store closures. Wide variety of models with sufficient accuracy were created by participants from various departments and occupations. We also administer a participant survey and participants answered that the improving their technical capabilities through the competition. Thus, the in-house competition not only solves the problem of insufficient staff and resource constraints on the part of the organizer, but also improves the technical skills of the participants.