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. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Shi, Z., Melli, G., Wang, Y., Liu, Y., Gu, B., Kashani, M. M., … Popowich, F. (2007). Question answering summarization of multiple biomedical documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4509 LNAI, pp. 284–295). Springer Verlag. https://doi.org/10.1007/978-3-540-72665-4_25
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