A Multilingual Study of Multi-Sentence Compression using Word Vertex-Labeled Graphs and Integer Linear Programming
Table 6: ROUGE F-measure results on the French, Portuguese and Spanish corpora. The best ROUGE results are in bold.
['[BOLD] Metrics', '[BOLD] Methods F10', '[BOLD] Methods BM13', '[BOLD] Methods ILP:80%', '[BOLD] Methods ILP:80%+LM', '[BOLD] Methods ILP:∞', '[BOLD] Methods ILP:∞+LM']
Based on these results, a further analysis was done for the 80% and ∞ configurations. The first two columns display the evaluation of the two baseline systems; the ROUGE scores measured with our method using either 80% or ∞ maximum compression lengths are shown in the next two columns and the last two columns respectively. The outputs produced by all of these systems for two sample clusters in Spanish and Portuguese can be found in the Appendix. Globally, all versions of our ILP method outperform both baselines according to ROUGE F-measures for the Portuguese and Spanish corpora, and our ILP systems (ILP:80% and ILP:∞) obtained similar results to BM13 for the French corpus. The POS-LM post-processing further improved the ROUGE scores for Portuguese and Spanish, but unfortunately not for the French corpus.