While participating in the HARD track our first question was, what an IR-application should look like that takes into account preference meta-data from the user, without the need ...
Recommender systems are important to help users select relevant and personalised information over massive amounts of data available. We propose an unified framework called Prefer...
As microblogging grows in popularity, services like Twitter are coming to support information gathering needs above and beyond their traditional roles as social networks. But most...
Daniel Ramage, Susan T. Dumais, Daniel J. Liebling
In this work, we present a constrained-based representation for specifying the goals of “course design”, that we call curricula model, and introduce a graphical language, groun...
We describe an efficient learning algorithm for aligning a symbolic representation of a musical piece with its acoustic counterpart. Our method employs a supervised learning appr...