Our central claim is that user interactions with everyday productivity applications (e.g., word processors, Web browsers, etc.) provide rich contextual information that can be lev...
Abstract This paper investigates whether a machine can automatically learn the task of finding, within a large collection of candidate responses, the answers to questions. The lea...
Adam L. Berger, Rich Caruana, David Cohn, Dayne Fr...
We address the issue of detecting automatically occurrences of high level patterns in audiovisual documents. These patterns correspond to recurring sequences of shots, which are co...
This paper explores the possibility to exploit text on the world wide web in order to enrich the concepts in existing ontologies. First, a method to retrieve documents from the WWW...
Eneko Agirre, Olatz Ansa, Eduard H. Hovy, David Ma...
Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis of count data. Fit...