Co-occurrence Mapping between Chinese Library Classification and International Patent Classification Categories Based on Author's Research Similarity
Knowledge flow between papers and patents reflects the evolutionary route of scientific research and technolog-ical innovation.Category mapping analysis of Chinese Library Classification(CLC)and International Patent Classification(IPC)is helpful in breaking through the barriers between paper and patent resources,by identifying the characteristics of scientific and technological development between papers and patents of different disciplines.This study proposes a map-ping method that integrates the idea of social network analysis with co-occurrence mapping.Taking the papers and patents of the same author and highly related research topics as unit data,CLC and IPC are used to classify and label each unit of data simultaneously,thereby combining category similarity calculations and analyzing the labeling results of the dataset.Fi-nally,universal one-to-one,one-to-many,and two-way mappings between the CLC and IPC categories are obtained.
NETL
NSTL
万方数据
