Abstract
With the aim to deal with sentiment-transfer problem, we proposed a novel approach, which integrates the sentiment orientations of documents into the graph-ranking algorithm. We apply the graph-ranking algorithm using the accurate labels of old-domain documents as well as the "pseudo" labels of new-domain documents. Experimental results show that proposed algorithm could improve the performance of baseline methods dramatically for sentiment transfer. © 2009 ACL and AFNLP.
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CITATION STYLE
Wu, Q., Tan, S., & Cheng, X. (2009). Graph ranking for sentiment transfer. In ACL-IJCNLP 2009 - Joint Conf. of the 47th Annual Meeting of the Association for Computational Linguistics and 4th Int. Joint Conf. on Natural Language Processing of the AFNLP, Proceedings of the Conf. (pp. 317–320). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1667583.1667681
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