We study a novel shallow information extraction problem that involves extracting sentences of a given set of topic categories from medical forum data. Given a corpus of medical fo...
We present a two-step method to speed-up object detection systems in computer vision that use Support Vector Machines (SVMs) as classifiers. In a first step we perform feature red...
Bernd Heisele, Thomas Serre, Sayan Mukherjee, Toma...
In this paper, we tackle the problem of characterizing the aesthetic appeal of consumer videos and automatically classifying them into high or low aesthetic appeal. First, we condu...
Defining and using ontology to annotate web resources with semantic markups is generally perceived as the primary way to implement the vision of the Semantic Web. The ontology prov...
We approached the problem as learning how to order documents by estimated relevance with respect to a user query. Our support vector machines based classifier learns from the rele...
Dmitri Roussinov, Weiguo Fan, Fernando A. Das Neve...