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.
CITATION STYLE
Sano, S., Kaji, N., & Sassano, M. (2016). Prediction of prospective user engagement with intelligent assistants. In 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Long Papers (Vol. 2, pp. 1203–1212). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/p16-1114
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