Enumeration of extractive oracle summaries

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Abstract

To analyze the limitations and the future directions of the extractive summarization paradigm, this paper proposes an Integer Linear Programming (ILP) formulation to obtain extractive oracle summaries in terms of ROUGEn. We also propose an algorithm that enumerates all of the oracle summaries for a set of reference summaries to exploit F-measures that evaluate which system summaries contain how many sentences that are extracted as an oracle summary. Our experimental results obtained from Document Understanding Conference (DUC) corpora demonstrated the following: (1) room still exists to improve the performance of extractive summarization; (2) the F-measures derived from the enumerated oracle summaries have significantly stronger correlations with human judgment than those derived from single oracle summaries.

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APA

Hirao, T., Nishino, M., Suzuki, J., & Nagata, M. (2017). Enumeration of extractive oracle summaries. In 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference (Vol. 1, pp. 386–396). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/e17-1037

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