Abstract
It is important for researchers/investigators to read and understand scientific papers effectually and effectively. However, it takes much time and many efforts to read and understand many papers related directly to their researches, even if they could refer to necessary papers timely. In this paper, we address a function for supporting the scientific paper understanding process successfully. We focus on figures which can usually explain the important topics along a series of successive paragraphs, and develop an intellectual tool which collects the mutually related sentences, attended interdependently to the focused figure, and supports a paper understanding ability through the focused figure. In this paper, we introduce the propagation mechanism of important words over the corresponding sentences. This propagation mechanism can select candidate sentences appropriate to explain the focused figure.
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These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Takeshima, R., Watanabe, T. (2010). Extraction of Co-existent Sentences for Explaining Figures toward Effective Support for Scientific Papers Reading. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6279. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15384-6_25
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DOI: https://doi.org/10.1007/978-3-642-15384-6_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15383-9
Online ISBN: 978-3-642-15384-6
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