We demonstrate a method for collaborative ranking of future events. Previous work on recommender systems typically relies on feedback on a particular item, such as a movie, and ge...
Einat Minkov, Ben Charrow, Jonathan Ledlie, Seth J...
We present a metadata free system for the interaction with massive collections of music, the MusicSurfer. MusicSurfer automatically extracts descriptions related to instrumentatio...
Many factorization models like matrix or tensor factorization have been proposed for the important application of recommender systems. The success of such factorization models dep...
When users combine data from multiple sources into a spreadsheet or dataset, the result is often a mishmash of different formats, since phone numbers, dates, course numbers and ot...
This paper presents a new way of thinking for IR metric optimization. It is argued that the optimal ranking problem should be factorized into two distinct yet interrelated stages:...