PCサイトを見る

ニュース・イベント

受賞

修了生のLINさんが日本デザイン学会第3支部奨励賞を受賞

 修了生のLIN, Yung Yuさん(令和3年3月後期課程修了、ヒューマンライフデザイン領域、永井研究室)が日本デザイン学会第3支部奨励賞を受賞しました。

 日本デザイン学会第3支部奨励賞は、日本デザイン学会第3支部会員(教員)在籍の大学院、大学、短期大学において、特に優秀な研究、制作を行った学生、大学院生に対して授与されるものです。

■受賞年月日
 令和3年3月26日

■研究題目、論文タイトル等
Oriented Development of Enterprise Message Management: Study on Visual Attention of Email Topic Inference (AttLDA for Email) and Integration of ECS and ERP (SuccERP)

■受賞対象となった研究の内容
Our dissertation is mainly focusing on several topics for improving collaboration and communication in an enterprise. Come with considering two features of collaboration, unstructured collaboration (information collaboration) and structured collaboration (process collaboration); we primarily focus on two representative applications: email and Enterprise Resource Planning (ERP) System.
In terms of an enterprise, most of the current research result struggles to achieve specific and practical goals by proposed theoretical findings in the ERP domain. To allow the managers to get a fuller picture of all the messages generated from an ERP system with the Enterprise Collaboration System (ECS) and improve collaboration and communication, we propose a complete method to develop an artifact-SuccERP based on the Design Science approach to carry out the integration. Based on exploring multiple ERP systems, we summarize our tasks into three aspects before implementing the integrations: authentication, data initialization, and specific procedures implementation; we also explain how the data-processing and integrations between the ERP and ECS. Next, the definition of information collaboration is employees applying IT tools to communicate and request assistance (answer); email is the most standard documentation tool for communication. Although existing studies use the topic model to support users for classifying emails, they disregard that humans are not like a machine that can focus on all the words in an email to determine the distribution of email topics. The Latent Dirichlet Allocation (LDA) model forms a basis for inferring topics; our work aims to discover how each word's visual attention influences the topic inference and estimates attention to a word according to its location features.

■受賞にあたって一言
It is a great honor to receive this award from JSSD (Japanese Society for the Science of Design). JAIST provides researchers abundant resources and robust research strength. Meanwhile, I would like to appreciate my supervisor, Prof. Yukari Nagai, for supporting and give me so many suggestions on my research field.

award20210420-1.jpg

令和3年4月20日

PAGETOP