Enumeration of Extractive Oracle Summaries

January 06, 2017 ยท Declared Dead ยท ๐Ÿ› Conference of the European Chapter of the Association for Computational Linguistics

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Authors Tsutomu Hirao, Masaaki Nishino, Jun Suzuki, Masaaki Nagata arXiv ID 1701.01614 Category cs.CL: Computation & Language Citations 16 Venue Conference of the European Chapter of the Association for Computational Linguistics Last Checked 3 months ago
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 ROUGE-N. 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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