主催: Shizuoka Univesity
会議名: 14th International Conference on Global Research and Education, Inter-Academia 2015
開催地: Hamamatsu, Japan
開催日: 2015/09/28 - 2015/09/30
Mathematical expressions are indispensable for describing mathematical concepts or models. Although these expressions are formal representations, they contain ambiguity, i.e., a single expression could be interpreted as having multiple meanings. This feature prevents the flexible use of mathematical expressions in computation. In this paper, we focus on symbol-level ambiguity and consider the problem of labeling semantic information to each symbol as a classification problem. Then we propose a framework for solving the problem with supervised learning.