Word Graph-Based Multi-sentence Compression: Re-ranking Candidates Using Frequent Words

Multi-Sentence Compression is a task whose goal is to produce a short single sentence summary from a group of similar sentences. This paper presents a new re-ranking method based on frequent words extraction along with our modifications on a word graph-based MSC approach to reduce incorrect output. Compression candidates are re-ranked according to the number of frequent words they contain to select the most relevant output. Results of automatic evaluations performed in English and Vietnamese datasets show that the proposed method remarkably improves the generated compressions informativity.

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