Improve classification on infrequent discourse relations via training data enrichment
Discourse parsing is a popular technique widely used in text understanding, sentiment analysis, and other NLP tasks. However, for most discourse parsers, the performance varies significantly across different discourse relations. In this thesis, we first validate the underfitting hypothesis, i.e., th...
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| Language: | English |
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University of British Columbia
2016
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| Online Access: | http://hdl.handle.net/2429/59844 |
