NSTL Intelligent Literature Services
Loading...
Date
Authors
Xia, Chunzi
Liu, Yao
Journal Title
Journal ISSN
Volume Title
Publisher
International Federation of Library Associations and Institutions (IFLA)
Abstract
Our research in recent years has centered on unlocking the full value of AI-empowered research to boost the efficiency, depth and innovation potential of academic exploration. Unlike traditional keyword-based retrieval methods that suffer from limited accuracy and contextual deficiency, our work enables smarter research search through advanced semantic and contextual understanding of academic resources, allowing researchers to capture essential information beyond literal text matches. Furthermore, our research focuses on facilitating efficient knowledge acquisition by rapidly locating, synthesizing and integrating scattered academic information, and delivering targeted, valuable insights to streamline researchers’ knowledge sorting and learning process. Beyond efficient information retrieval and knowledge digestion, our core research also lies in providing robust innovation support for academic research: by leveraging AI technologies to mine massive research data, we are able to uncover hidden correlations, potential rules and emerging research trends within disciplinary knowledge systems, which effectively inspires novel research perspectives and creative ideas to drive continuous academic innovation.