  With the recent development of technology, data on detailed human temporal
behaviors has become available. Many methods have been proposed to mine those
human dynamic behavior data and revealed valuable insights for research and
businesses. However, most methods analyze only sequence of actions and do not
study the inter-temporal information such as the time intervals between actions
in a holistic manner. While actions and action time intervals are
interdependent, it is challenging to integrate them because they have different
natures: time and action. To overcome this challenge, we propose a unified
method that analyzes user actions with intertemporal information (time
interval). We simultaneously embed the user's action sequence and its time
intervals to obtain a low-dimensional representation of the action along with
intertemporal information. The paper demonstrates that the proposed method
enables us to characterize user actions in terms of temporal context, using
three real-world data sets. This paper demonstrates that explicit modeling of
action sequences and inter-temporal user behavior information enable successful
interpretable analysis.
