A context-aware study for sentence ordering

This paper proposes a context-aware method for sentence ordering in multi-document summarization task, which combines support vector machine (SVM) and Grey Model (GM). Multi-Documents summarization task focus on how to extract main information of document set, this paper aim to prove the coherence of summary based on the context of document set. Firstly, the method trains the SVM with sentences of each source document and predict sentences sequence of summary as primary dataset. Secondly, using Grey Model to process the primary dataset, according to the analysis we achieve the final sequence of summary sentences. Experiments on 100 summaries shown this method provide a much higher precision than probabilistic model in sentence ordering task.