Many social networks can be characterized by a sequence of dyadic interactions between individuals. Techniques for analyzing such events are of increasing interest. In this paper,...
While a user’s preference is directly reflected in the interactive choice process between her and the recommender, this wealth of information was not fully exploited for learni...
Shuang-Hong Yang, Bo Long, Alexander J. Smola, Hon...
Increasingly, organizations have been investing heavily in information systems for greater dyadic coordination and cooperation with each of their key business partners. In this re...
Discrete mixed membership modeling and continuous latent factor modeling (also known as matrix factorization) are two popular, complementary approaches to dyadic data analysis. In...
We developed a new model for iList, our system that helps students learn linked list. The model is automatically extracted from past student data, and allows iList to track student...
Davide Fossati, Barbara Di Eugenio, Stellan Ohlsso...