2004 Presentations (Communicative Events)
Event-Based Extractive Summarization
Most approaches to extractive summarization define a set of features upon which selection of sentences is based, using algorithms independent of the features themselves. We propose a new set of features based on low-level, atomic events that describe relationships between important actors in a document or set of documents. We investigate the effect this new feature has on extractive summarization, compared with a baseline feature set consisting of the words in the input documents, and with state-of-the-art summarization systems. Our experimental results indicate that not only the event-based features offer an improvement in summary quality over words as features, but that this effect is more pronounced for more sophisticated summarization methods that avoid redundancy in the output.
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filatova_hatzivassiloglou_04a.pdf application/pdf 127 KB Download File
More About This Work
- Academic Units
- Computer Science
- Publisher
- ACL Workshop on Summarization
- Published Here
- May 30, 2013