JSAI2020

Presentation information

Interactive Session

[4Rin1] Interactive 2

Fri. Jun 12, 2020 9:00 AM - 10:40 AM Room R01 (jsai2020online-2-33)

[4Rin1-12] Synthesis Process Paragraph Extraction from Scientific Literature of Inorganic Material

〇Kohei Makino1,3, Fusataka Kuniyoshi2,3, Jun Ozawa2,3, Makoto Miwa1,3 (1.Toyota Technological Institute, 2.Panasonic Corporation, 3.National Institute of Advanced Industrial Science and Technology)

Keywords:Paragraph Extraction, Natural Language Processing, Materials Informatics

In the field of inorganic materials, there is a need for a system that supports development by analyzing synthesis processes described in a large number of papers. In order to realize the system, it is necessary to extract the part where synthesis processes are described from the papers. We propose a tool that extracts paragraphs describing synthesis processes from papers in the PDF format. We develop the tool by combining a deep learning-based sentence classifier that determines whether each sentence includes synthesis processes or not and a paragraph detector using the sentence classifier. In the experiment, we evaluated our tool on manually-labeled 300 papers. As a result, our tool performed well in both classifying sentences and detecting paragraphs. This result shows that the proposed tool is useful in extracting paragraphs on synthesis processes.

Authentication for paper PDF access

A password is required to view paper PDFs. If you are a registered participant, please log on the site from Participant Log In.
You could view the PDF with entering the PDF viewing password bellow.

Password