Scientists depend on literature search to find prior work that is relevant to their research ideas. We introduce a retrieval model for literature search that incorporates a wide ...
Online social networks often involve very large numbers of users who share very large volumes of content. This content is increasingly being tagged with geo-spatial and temporal c...
Dario Freni, Carmen Ruiz Vicente, Sergio Mascetti,...
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 propose and evaluate a probabilistic framework for estimating a Twitter user’s city-level location based purely on the content of the user’s tweets, even in the absence of ...
Personalized search systems have evolved to utilize heterogeneous features including document hyperlinks, category labels in various taxonomies and social tags in addition to free...