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Domain Adaptation for Dependency Parsing via Self-Training
2015
Proceedings of the 14th International Conference on Parsing Technologies
This paper presents a successful approach for domain adaptation of a dependency parser via self-training. We improve parsing accuracy for out-of-domain texts with a self-training approach that uses confidence-based methods to select additional training samples. We compare two confidence-based methods: The first method uses the parse score of the employed parser to measure the confidence into a parse tree. The second method calculates the score differences between the best tree and alternative
doi:10.18653/v1/w15-2201
dblp:conf/iwpt/YuEB15
fatcat:poy6w2srhrcmdh3peosn2m4oly