A compact representation for cross-domain short text clustering

Abstract

Supervised classification strategies, assume that training and test documents are drawn from the same distribution. However, in many cases this scenario is unreal, especially in data sets extracted from Twitter. Thus, the process of using a statistical model trained in one (source) domain, for categorizing information contained in a different (target) domain, requires bridging the gab between the two domains to facilitate the knowledge transfer.