Development of Big Data Research Analytic Software

Description

Heterogeneous research data (e.g., projects, publications, and patents) is of great value to research and innovation. Innovation knowledge graph is also proposed to extract the heterogeneous data from research social network platform. Based on which, this project aims to develop big data research analytic software for research and innovation applications. Methodologies such as big data research analytics, machine learning, and natural language processing will be used to extract knowledge from the increasingly large set of heterogeneous research data. The project will be carried out based on a research social network platform, i.e., www.ScholarMate.com, with more than 3.6 million researchers, and 42 million research outputs (including publication and patents with full text and datasets). The project outcomes, i.e., big data research analytic software will find wide applications in supporting research and innovation activities.