- 一般社団法人 人工知能学会
- 人工知能学会論文誌 (ISSN:13460714)
- vol.33, no.4, pp.A-H91_1-13, 2018-07-01 (Released:2018-07-02)
Recently the importance of mathematical information retrieval (MIR) has been recognized and various methods for mathematical expression retrieval have also been proposed. However, since mathematical expressions on the Web are not annotated with natural language, searching for mathematical expressions by conventional search engines is difficult. For helping people in various fields who use mathematics as a learning tool, our proposed method performs a Web search using a mathematical term as a query, extracts mathematical expression images (math-images) related to the query from the obtained Web pages, and presents the top ten math-images with their surrounding information. The method measures the relevance between a query and a math-image from the following viewpoints: the math-image is in a separate line, it has the query in the neighborhood and appropriate image feature quantities, and it appears in the first part of the Web page. We use a support vector machine to discriminate if the image provides appropriate feature quantities. We conducted two experiments with our proposed method. We determined its scoring parameters in Experiment 1 and evaluated it in Experiment 2. The results revealed the usefulness of our proposed method with accuracy, recall, F-measure, mean reciprocal rank (MRR), and mean average precision (MAP).