Our goal is to predict the sentiment polarity of the examples in a target language-domain pair In Section 5 we compare two CLIDSA variants.
cLIDSA f ull exploits unlabeled data from all possible language-domain pairs, i.e., we set P = L × D. since most previous cLSA methods do not use multi-domain or multilingual unlabeled data, we create a variant cLIDSA min that requires minimal resources by setting A natural way to utilize unlabeled data is to perform the language modeling task.