2007 QASummaOfMultBiomedDocs

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Subject Headings: Text Summarization Task, Biomedical Discipline.


Cited By



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.



 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2007 QASummaOfMultBiomedDocsGabor Melli
Fred Popowich
Yang Wang
Zhongmin Shi
Yudong Liu
Anoop Sarkar
Mehdi M. Kashani
Baohua Gu
Question Answering Summarization of Multiple Biomedical Documentshttp://www.cs.sfu.ca/~anoop/papers/pdf/biosquash.pdf