Dataset for "Towards Automated Related Work Summarization"

Abstract

<p><strong>Please ensure the following paper is cited appropriately when you reuse this dataset.</strong> For more details, please refer to Citation field.</p> <ul> <li> <a href="http://anthology.aclweb.org/C/C10/C10-2049.pdf">Cong Duy Vu Hoang and Min-Yen Kan (2010) Towards Automated Related Work Summarization. In Proceedings of the 23rd International Conference on Computational Linguistics (COLING 2010), Beijing, China. pp. 427-435.</a> </li> </ul> <p> We introduce the novel problem of automatic related work summarization. Given multiple articles (e.g., conference/journal papers) as input, a related work summarization system creates a topic-biased summary of related work specific to the target paper. Our prototype Related Work Summarization system, ReWoS, takes in set of keywords arranged in a hierarchical fashion that describes a target paper's topics, to drive the creation of an extractive summary using two different strategies for locating appropriate sentences for general topics as well as detailed ones. Our initial results show an improvement over generic multi-document summarization baselines in a human evaluation. </p> <p> For details, please visit <a href="https://github.com/WING-NUS/RelatedWorkSummarizationDataset">https://github.com/WING-NUS/RelatedWorkSummarizationDataset</a> </p>