Papers by Eneldo Loza Mencía

2 papers
A Data Set for the Analysis of Text Quality Dimensions in Summarization Evaluation (2020.lrec-1)

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Challenge: Existing methods for summarization evaluation focus on a metric to represent the quality of the text, but they focus on only a few quality dimensions.
Approach: They analyze the depen-dencies between various quality dimensions on automatically created multi-document summaries and which are best suited for summarization.
Outcome: The proposed method achieves higher quality summaries than other methods on a large-scale heterogeneous data set.
Which Scores to Predict in Sentence Regression for Text Summarization? (N18-1)

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Challenge: Sentence regression is an emerging branch in automatic text summarizations.
Approach: They propose to estimate the importance of information via learned utility scores for individual sentences.
Outcome: The proposed models learn to predict ROUGE recall scores of individual sentences . the models show that following intuition leads to suboptimal results .

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