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 ...
Background: During the most recent decade many Bayesian statistical models and software for answering questions related to the genetic structure underlying population samples have...