論 文Papers

CONFERENCE (INTERNATIONAL)

Prediction of Prospective User Engagement with Intelligent Assistants

Shumpei Sano, Nobuhiro Kaji, and Manabu Sassano

ACL2016 (the annual meeting of the Association for Computational Linguistics), 2016/8

Category:

自然言語処理 (Natural Language Processing) 機械学習 (Machine Learning) データサイエンス (Data Science)

Abstract:
Intelligent assistants on mobile devices, such as Siri, have recently gained considerable attention as novel applications of dialogue technologies. A tremendous amount of real users of intelligent assistants provide us with an opportunity to explore a novel task of predicting whether users will continually use their intelligent assistants in the future. We developed prediction models of prospective user engagement by using large-scale user logs obtained from a commercial intelligent assistant. Experiments demonstrated that our models can predict prospective user engagement reasonably well, and outperforms a strong baseline that makes prediction based past utterance frequency.
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