We propose Dual-CES - a novel unsupervised, query-focused, multi-document extractive summarizer. Dual-CES builds on top of the Cross Entropy Summarizer (CES) and is designed to better handle the tradeoff between saliency and focus in summarization. To this end, Dual-CES employs a two-step dual-cascade optimization approach with saliency-based pseudo-feedback distillation. Overall, Dual-CES significantly outperforms all other state-of-the-art unsupervised alternatives. Dual-CES is even shown to be able to outperform strong supervised summarizers.
|Title of host publication||The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020|
|Publisher||Association for Computing Machinery, Inc|
|Number of pages||8|
|State||Published - 20 Apr 2020|
|Event||29th International World Wide Web Conference, WWW 2020 - Taipei, Taiwan, Province of China|
Duration: 20 Apr 2020 → 24 Apr 2020
|Name||The Web Conference 2020 - Proceedings of the World Wide Web Conference, WWW 2020|
|Conference||29th International World Wide Web Conference, WWW 2020|
|Country/Territory||Taiwan, Province of China|
|Period||20/04/20 → 24/04/20|
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