Abstract
In this paper we introduce a system that automatically summarizes multiple biomedical documents relevant to a question. The system extracts biomedical and general concepts by utilizing concept-level knowledge from domain-specific and domain-independent sources. Semantic role labeling, semantic subgraph-based sentence selection and automatic post-editing are involved in the process of finding the information need. Due to the absence of expert-written summaries of biomedical documents, we propose an approximate evaluation by taking MEDLINE abstracts as expert-written summaries. Evaluation results indicate that our system does help in answering questions and the automatically generated summaries are comparable to abstracts of biomedical articles, as evaluated using the ROUGE measure.
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References
Mani, I., Bloedorn, E.: Summarizing similarities and differences among related documents. Information Retrieval 1(1), 1–23 (1999)
Damianos, L., Day, D., Hirschman, L., Kozierok, R., Mardis, S., McEntee, T., McHenry, C., Miller, K., Ponte, J., Reeder, F., van Guilder, L., Wellner, B., Wilson, G., Wohlever, S.: Real users, real data, real problems: the mitap system for monitoring bio events. In: Proceedings of BTR2002, The University of New Mexico (March 2004)
Gaizauskas, R., Herring, P., Oakes, M., Beaulieu, M., Willett, P., Fowkes, H., Jonsson, A.: Intelligent access to text: integrating information extraction technology into text browsers. In: Proceedings of HLT 2001, San Diego, pp. 189–193 (2001)
Kan, M., McKeown, K., Klavans, J.: Domain-specific informative and indicative summarization for information retrieval. In: Workshop on text summarization (DUC 2001), New Orleans (2001)
Elhadad, N., McKeown, K.: Towards generating patient specific summaries of medical articles. In: Proceedings of automatic summarization workshop (NAACL 2001), Pittsburgh, PA, USA (2001)
Melli, G., Wang, Y., Liu, Y., Kashani, M., Shi, Z., Gu, B., Sarkar, A., Popowich, F.: Description of squash, the sfu question answering summary handler for the duc-2005 summarization task. In: Proceeding of DUC-2005, Vancouver, Canada, October 2005, pp. 103–110 (2005)
Charniak, E.: A maximum-entropy-inspired parser. In: Meeting of the North American Chapter of the ACL, pp. 132–139 (2000)
Gildea, D., Jurafsky, D.: Automatic labeling of semantic roles. Computational Linguistics 28(3), 245–288 (2002)
Palmer, M., Gildea, D., Kingsbury, P.: The proposition bank: An annotated corpus of semantic roles. Computational Linguistics 31(1) (2005)
Liu, Y., Sarkar, A.: Using ltag-based features for semantic role labeling. In: Proceedings of the Eighth Workshop on Tree Adjoining Grammars and Related Formalisms: TAG+8, Poster Track, Sydney, Australia (July 2006)
Kingsbury, P., Palmer, M.: From treebank to propbank. In: Proceedings of the 3rd International Conference on Language Resources and Evaluation, LREC-2002 (2002)
Pedersen, T., Banerjee, S., Patwardhan, S.: Maximizing semantic relatedness to perform word sense disambiguation. University of Minnesota Supercomputing Institute Research Report (March 2005)
Mani, I., Bloedorn, E.: Multi-document summarization by graph search and matching. In: Proceedings of the 14th National Conference on Artificial Intelligence, Providence, Rhode Island, pp. 622–628 (1997)
Shi, Z., Gu, B., Popowich, F., Sarkar, A.: Synonym-based query expansion and boosting-based re-ranking: A two-phase approach for genomic information rretrieval. In: The Fourteenth Text REtrieval Conference (TREC 2005), NIST, Gaithersburg, MD (October 2005)
Lin, C.Y., Hovy, E.H.: Automatic evaluation of summaries using n-gram co-occurrence statistics. In: Proceedings of Language Technology Conference (HLT-NAACL 2003), Edmonton, Canada (May 2003)
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Shi, Z. et al. (2007). Question Answering Summarization of Multiple Biomedical Documents. In: Kobti, Z., Wu, D. (eds) Advances in Artificial Intelligence. Canadian AI 2007. Lecture Notes in Computer Science(), vol 4509. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72665-4_25
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DOI: https://doi.org/10.1007/978-3-540-72665-4_25
Publisher Name: Springer, Berlin, Heidelberg
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