Kernel-based Approach for Automatic Evaluation of Natural Language Generation Technologies: Application to Automatic Summarization
نویسندگان
چکیده
In order to promote the study of automatic summarization and translation, we need an accurate automatic evaluation method that is close to human evaluation. In this paper, we present an evaluation method that is based on convolution kernels that measure the similarities between texts considering their substructures. We conducted an experiment using automatic summarization evaluation data developed for Text Summarization Challenge 3 (TSC-3). A comparison with conventional techniques shows that our method correlates more closely with human evaluations and is more robust.
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