We report on the development of a new automatic feedback model to improve information retrieval in digital libraries. Our hypothesis is that some particular sentences, selected ba...
Patrick Ruch, Imad Tbahriti, Julien Gobeill, Alan ...
Nowadays, searching information in the web or in any kind of document collection has become one of the most frequent activities. However, user queries can be formulated in a way th...
This paper explores the use of set expansion (SE) to improve question answering (QA) when the expected answer is a list of entities belonging to a certain class. Given a small set...
Richard C. Wang, Nico Schlaefer, William W. Cohen,...
Recent work has exploited boundedness of data in the unsupervised learning of new types of generative model. For nonnegative data it was recently shown that the maximum-entropy ge...
We give a O( log n)-approximation algorithm for sparsest cut, edge expansion, balanced separator, and graph conductance problems. This improves the O(log n)-approximation of Leig...