Generating indicative-informative summaries with sumUM
Computational Linguistics - Summarization
Experiments in multidocument summarization
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Design and development of a concept-based multi-document summarization system for research abstracts
Journal of Information Science
Multi-document summarization by sentence extraction
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization
Arabic/English multi-document summarization with CLASSY: the past and the future
CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Towards automated related work summarization
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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This paper gives an overview of a project to generate literature reviews from a set of research papers, based on techniques drawn from human summarization behavior. For this study, we identify the key features of natural literature reviews through a macro-level and clause-level discourse analysis; we also identify human information selection strategies by mapping referenced information to source documents. Our preliminary results of discourse analysis have helped us characterize literature review writing styles based on their document structure and rhetorical structure. These findings will be exploited to design templates for automatic content generation.