Proceedings of the Annual Conference of JSAI
Online ISSN : 2758-7347
32nd (2018)
Session ID : 4A2-05
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Newcomers churn prediction by the event sequence on social networking service
*Koya SATOMizuki OKAKazuhiko KATO
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CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

To be sustainable the social networking service, newcomer churn prediction is an important task. Previous churn prediction models use handcrafted and service-specific features. Therefore, it is difficult to apply developed the model to other similar social networking services. To solve this, we propose new deep learning method that doesn't depend on specific service.

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© 2018 The Japanese Society for Artificial Intelligence
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