Evaluation of Cross Domain Text Summarization

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Abstract

Extractive-abstractive hybrid summarization can generate readable, concise summaries for long documents. Extraction-then-abstraction and extraction-with-abstraction are two representative approaches to hybrid summarization. But their general performance is yet to be evaluated by large scale experiments.We examined two state-of-the-art hybrid summarization algorithms from three novel perspectives: we applied them to a form of headline generation not previously tried, we evaluated the generalization of the algorithms by testing them both within and across news domains; and we compared the automatic assessment of the algorithms to human comparative judgments. It is found that an extraction-then-abstraction hybrid approach outperforms an extraction-with-abstraction approach, particularly for cross-domain headline generation.

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Scanlon, L., Zhang, S., Zhang, X., & Sanderson, M. (2020). Evaluation of Cross Domain Text Summarization. In SIGIR 2020 - Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 1853–1856). Association for Computing Machinery, Inc. https://doi.org/10.1145/3397271.3401285

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