The continuously increasing cost of the US healthcare system has received significant
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …

The ability to predict future user activity is invaluable when it comes to content
recommendation and personalization. For instance, knowing when users will return to an …

By making personalized suggestions, a recommender system is playing a crucial role in
improving the engagement of users in modern web-services. However, most …

Repeat consumption is a common scenario in daily life, such as repurchasing items and
revisiting websites, and is a critical factor to be taken into consideration for recommender …

Event prediction in the continuous-time domain is a crucial but rather difficult task. Temporal
point process (TPP) learning models have shown great advantages in this area. Existing …

In this work, we propose to improve long-term user engagement in a recommender system
from the perspective of sequential decision optimization, where users' click and return …

We study sequences of consumption in which the same item may be consumed multiple
times. We identify two macroscopic behavior patterns of repeated consumptions. First, in a …

The study of career development has become more important during a time of rising
competition. Even with the help of newly available big data in the field of human resources, it …

Repeat purchasing, ie, a customer purchasing the same product multiple times, is a common
phenomenon in retail. As more customers start purchasing consumable products (eg …

While mobile social apps have become increasingly important in people's daily life, we have
limited understanding on what motivates users to engage with these apps. In this paper, we …