Enrique Cuan

We don’t have enough information about this author to calculate their statistics. If you think this is an error let us know.
Learn More
The development of a sentiment classifier experiences two problems to cope with: the demand of large amounts of labelled training data and a decrease in performance when the classifier is applied to a different domain. In this paper, we attempt to address this problem by exploring a number of metrics that try to predict the cross-domain performance of a(More)
The adaptation problem in sentiment classification is approached in this paper. Since the availability of labeled data required by sentiment classifiers is not always possible, given a set of labeled data from different domains and a small amount of labeled data of the target domain, it would be interesting to determine which subset of those domains has a(More)
  • 1