2017
EACL
EACL 2017
Improving ROUGE for Timeline Summarization
Abstract
AbstractCurrent evaluation metrics for timeline summarization either ignore the temporal aspect of the task or require strict date matching. We introduce variants of ROUGE that allow alignment of daily summaries via temporal distance or semantic similarity. We argue for the suitability of these variants in a theoretical analysis and demonstrate it in a battery of task-specific tests.
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Interdisciplinary Bridge
— Machine Learning and Mathematics & Optimization and Natural Language Processing
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Trend Setter
— Evaluation
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Keyword Pioneer
— summarization evaluation
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Hot Topic Early Bird
— summarization evaluation
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Security & Privacy, Speech & Audio