人工知能学会全国大会論文集
32nd (2018)
セッションID: 4A2-05
会議情報

Newcomers churn prediction by the event sequence on social networking service
*Koya SATOMizuki OKAKazuhiko KATO
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会議録・要旨集 フリー

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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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