The use of MMR, diversity-based reranking for reordering documents and producing summaries
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Summarization beyond sentence extraction: a probabilistic approach to sentence compression
Artificial Intelligence
Summarizing scientific articles: experiments with relevance and rhetorical status
Computational Linguistics - Summarization
Frequent term-based text clustering
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
The automated acquisition of topic signatures for text summarization
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
Centroid-based summarization of multiple documents
Information Processing and Management: an International Journal
The Knowledge Grid
Bayesian query-focused summarization
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Blind men and elephants: What do citation summaries tell us about a research article?
Journal of the American Society for Information Science and Technology
Whetting the appetite of scientists: producing summaries tailored to the citation context
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Scientific paper summarization using citation summary networks
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Automatic classification of citation function
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Topic-driven multi-document summarization with encyclopedic knowledge and spreading activation
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Using citations to generate surveys of scientific paradigms
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
Towards multi-paper summarization reference information
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Multi-document summarization by maximizing informative content-words
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Document summarization using conditional random fields
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Manifold-ranking based topic-focused multi-document summarization
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Identifying non-explicit citing sentences for citation-based summarization
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Citation summarization through keyphrase extraction
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Semantic linking through spaces for cyber-physical-socio intelligence: A methodology
Artificial Intelligence
SciSumm: a multi-document summarization system for scientific articles
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Systems Demonstrations
Coherent citation-based summarization of scientific papers
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Probabilistic Resource Space Model for Managing Resources in Cyber-Physical Society
IEEE Transactions on Services Computing
A text scanning mechanism simulating human reading process
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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Reading scientific articles is more time-consuming than reading news because readers need to search and read many citations. This paper proposes a citation guided method for summarizing multiple scientific papers. A phenomenon we can observe is that citation sentences in one paragraph or section usually talk about a common fact, which is usually represented as a set of noun phrases co-occurring in citation texts and it is usually discussed from different aspects. We design a multi-document summarization system based on common fact detection. One challenge is that citations may not use the same terms to refer to a common fact. We thus use term association discovering algorithm to expand terms based on a large set of scientific article abstracts. Then, citations can be clustered based on common facts. The common fact is used as a salient term set to get relevant sentences from the corresponding cited articles to form a summary. Experiments show that our method outperforms three baseline methods by ROUGE metric.