Host: The Japanese Society for Artificial Intelligence
Name : 34th Annual Conference, 2020
Number : 34
Location : Online
Date : June 09, 2020 - June 12, 2020
These days many companies try to use communication data on business chat systems for the management of human resources. Especially, the reply time between a talker and a receiver is affected by the relationship with the receiver desired to establish. Therefore, the analysis model about the reply time between two employees as the minimum unit with using a chat system should be effective. In this research, we propose a latent class model that quantitatively expresses the relationship between the talker, the receiver and the reply time and analyze the communication characteristics from the viewpoint of the reply time. We can interpret the combination of high-dimensional data and the difference between user behavior by introducing multiple latent variables that are probabilistically occurred behind the observed variables. Finally, we apply the model to the real data of a Japanese company and show the usefulness of the model.