  In the era of big data, it is possible to carry out cooperative research on
the research results of researchers through papers, patents and other data, so
as to study the role of researchers, and produce results in the analysis of
results. For the important problems found in the research and application of
reality, this paper also proposes a research scholar interest mining algorithm
based on load centrality (LCBIM), which can accurately solve the problem
according to the researcher's research papers and patent data. Graphs of
creative algorithms in various fields of the study aggregated ideas, generated
topic graphs by aggregating neighborhoods, used the generated topic information
to construct with similar or similar topic spaces, and utilize keywords to
construct one or more topics. The regional structure of each topic can be used
to closely calculate the weight of the centrality research model of the node,
which can analyze the field in the complete coverage principle. The scientific
research cooperation based on the load rate center proposed in this paper can
effectively extract the interests of scientific research scholars from papers
and corpus.

Digital Libraries;Artificial Intelligence