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2022 Fiscal Year Final Research Report

Feature visualizer and detector for scientific texts

Research Project

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Project/Area Number 19K00850
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Review Section Basic Section 02100:Foreign language education-related
Research InstitutionThe University of Aizu

Principal Investigator

Blake John  会津大学, コンピュータ理工学部, 上級准教授 (80635954)

Co-Investigator(Kenkyū-buntansha) Mozgovoy Maxim  会津大学, コンピュータ理工学部, 上級准教授 (60571776)
Project Period (FY) 2019-04-01 – 2023-03-31
Keywordsscientific writing / genre awareness raising / rhetorical features / language features / information structure / pedagogic tool
Outline of Final Research Achievements

We have developed Feature Detection and Feature Visualization tools. The Feature Visualization tool comprises an annotated dataset of short research articles and a bank of multimodal materials which are displayed in the user interface of the Feature Visualizer. Here users can visualize particular rhetorical or language aspects, e.g. modality, tense and cohesion. Users then have the option to display additional multimodal explanations to understand the specific rhetorical or language features. In addition, two Feature Detection tools were created that can process student-submitted work. The first colorizes finite verb phrases according to one of twelve pedagogic tenses. The main feature detection tool enables users to gain feedback on deep grammatical features, namely information structure. The end weight, the information focus and information flow are automatically annotated, helping learners differentiate between unmarked, highly frequent usage and marked, rare usage.

Free Research Field

natural language processing

Academic Significance and Societal Importance of the Research Achievements

The primary aim of this project is to develop an online resource that could assist Japanese writers of short research articles in the field of computer science to understand the prototypical generic features in such articles. This is envisaged to help them climb the cline of competence more quickly.

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Published: 2024-01-30  

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