The probability that a term appears in relevant documents ( ) is a fundamental quantity in several probabilistic retrieval models, however it is difficult to estimate without rele...
This paper introduces the problem of matching people names to their corresponding social network identities such as their Twitter accounts. Existing tools for this purpose build u...
Gae-won You, Seung-won Hwang, Zaiqing Nie, Ji-Rong...
arrhythmias (extended abstract) Elisa Fromont, Ren´e Quiniou, Marie-Odile Cordier We are interested in using parallel universes to learn interpretable models that can be subseque...
In the past years, the theory and practice of machine learning and data mining have been focused on static and finite data sets from where learning algorithms generate a static m...
Abstract. We consider the problem of predicting how a user will continue a given initial text fragment. Intuitively, our goal is to develop a “tab-complete” function for natura...