Read Top News First: A Document Reordering Approach for Multi-Document News Summarization
This addresses the issue of neglecting document importance in multi-document summarization for news applications, though it is incremental as it builds on existing concatenation methods.
The paper tackled the problem of extractive multi-document news summarization by proposing a document reordering approach based on relative importance before concatenation, which outperformed previous state-of-the-art methods with more complex architectures.
A common method for extractive multi-document news summarization is to re-formulate it as a single-document summarization problem by concatenating all documents as a single meta-document. However, this method neglects the relative importance of documents. We propose a simple approach to reorder the documents according to their relative importance before concatenating and summarizing them. The reordering makes the salient content easier to learn by the summarization model. Experiments show that our approach outperforms previous state-of-the-art methods with more complex architectures.