ISSN : 1013-0799
The purpose of this study is to investigate cases of LLM-based interactive AI-based academic information services, which have been widely used recently, to find out the current status and possibility of using AI technology, and to suggest more advanced interactive AI academic information service strategies in the future. In order to achieve the purpose of the study, cases of interactive AI academic information services provided overseas and domestically along with major literature studies were investigated and analyzed, and major examples include Scispace, Elicit, Scopus AI, Dimensions Research GPT, and Writefull, comparing the core functions and differences of each service. As a result of the analysis, we proposed a user-friendly interface, reliable data-based information, personalized services tailored to the user context, academic data creation support, collaboration, network expansion, and data visualization and analysis functions as strategies to implement successful interactive AI academic information services.
