Abstract
Aspect-level sentiment classification aims to
determine the sentiment polarity of a sentence
towards an aspect. Due to the high cost in annotation, the lack of aspect-level labeled data
becomes a major obstacle in this area. On the
other hand, document-level labeled data like
reviews are easily accessible from online websites. These reviews encode sentiment knowledge in abundant contexts. In this paper, we
propose a Transfer Capsule Network (TransCap) model for transferring document-level
knowledge to aspect-level sentiment classi-
fication. To this end, we first develop an
aspect routing approach to encapsulate the
sentence-level semantic representations into
semantic capsules from both aspect-level and
document-level data. We then extend the dynamic routing approach to adaptively couple
the semantic capsules with the class capsules
under the transfer learning framework. Experiments on SemEval datasets demonstrate the
effectiveness of TransCap