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Exploring Joint Neural Model for Sentence Level Discourse Parsing and Sentiment Analysis
2017
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue
Discourse Parsing and Sentiment Analysis are two fundamental tasks in Natural Language Processing that have been shown to be mutually beneficial. In this work, we design and compare two Neural models for jointly learning both tasks. In the proposed approach, we first create a vector representation for all the text segments in the input sentence. Next, we apply three different Recursive Neural Net models: one for discourse structure prediction, one for discourse relation prediction and one for
doi:10.18653/v1/w17-5535
dblp:conf/sigdial/NejatCN17
fatcat:khab45b5mzfu7grcxej2lpoq54