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A PhD course graduate from JAIST, Dr. LIN received the JSSD Encouragement Prize in the 3rd Branch.

Dr. LIN, Yung Yu (graduated from the JAIST PhD course at March 2021, Nagai Lab of Human Life Design Area) received the JSSD Encouragement Prize in the 3rd Branch.

JSSD Encouragement Prize in the 3rd Branch is the award which the JSSD (Japanese Society for the Science of Design) recognizes students excellent design research and creative work.

■Date Awarded
March 26, 2021

Oriented Development of Enterprise Message Management: Study on Visual Attention of Email Topic Inference (AttLDA for Email) and Integration of ECS and ERP (SuccERP)

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.

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.


April 20, 2021