An extractive supervised two-stage method for sentence compression
نویسندگان
چکیده
We present a new method that compresses sentences by removing words. In a first stage, it generates candidate compressions by removing branches from the source sentence’s dependency tree using a Maximum Entropy classifier. In a second stage, it chooses the best among the candidate compressions using a Support Vector Machine Regression model. Experimental results show that our method achieves state-of-the-art performance without requiring any manually written rules.
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