Keisuke Yokoi1, Minh–Quoc Nghiem2, Yuichiroh Matsubayashi3, and Akiko Aizawa4
1 Department of Computer Science, University of Tokyo, Hongo 7–3–1, Bunkyo–ku, Tokyo, Japan (e–mail: kei–yoko@nii.ac.jp).
2 Department of Informatics, The Graduate University for Advanced Studies, Tokyo, Japan (e–mail: nqminh@nii.ac.jp).
3 National Institute of Informatics, Tokyo, Japan (e–mail: y–matsu@nii.ac.jp).
4 Department of Computer Science, University of Tokyo, Hongo 7–3–1, Bunkyo–ku, Tokyo, Japan and with National Institute of Informatics, Tokyo, Japan (e–mail: aizawa@nii.ac.jp).
]]> Manuscript received November 12, 2010.
Abstract
We found a way to use mathematical search to provide better navigation for reading papers on computers. Since the superficial information of mathematical expressions is ambiguous, considering not only mathematical expressions but also the texts around them is necessary. We present how to extract a natural language description, such as variable names or function definitions that refer to mathematical expressions with various experimental results. We first define an extraction task and constructed a reference dataset of 100 Japanese scientific papers by hand. We then propose the use of two methods, pattern matching and machine learning based ones for the extraction task. The effectiveness of the proposed methods is shown through experiments by using the reference set.
Key words: Natural language processing, mathematical expressions, pattern matching, machine learning.
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