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Towards answering biological questions with experimental evidence: automatically identifying text that summarize
1Department of Health Sciences, University of Wisconsin-Milwaukee, USA.
Abstract:
Images (i.e., figures) are important experimental evidence that are typically reported in bioscience full-text articles. Biologists need to access images to validate research facts and to formulate or to test novel research hypotheses. We propose to build a biological question answering system that provides experimental evidences as answers in response to biological questions. As a first step, we develop natural language processing techniques to identify sentences that summarize image content.
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