Abstract
According to the needs of scientific research project research and development, the research of cooperative team excavation methods was carried out. Aiming at the current difficulties in accurately and reliably defining and identifying cooperative research teams from co-author network, an improved Louvain algorithm that integrates core node recognition was proposed: Louvain-LSCR algorithm. Based on the analysis of the Louvain algorithm, considering the local topology of the node in the network and the communication range of the node, a new algorithm LSCR for core node identification was constructed. The LSCR algorithm and Louvain algorithm were merged to obtain a new and improved algorithm, Louvain-LSCR. In this algorithm, the leaf nodes in phase 1 of Louvain algorithm were first pruned to reduce calculations; then, seed nodes were selected according to the LSCR algorithm in phase 2. The experimental results on related datasets show that LSCR algorithm has certain advantages in identifying core nodes. The modularity of Louvian-LSCR algorithm is better than other algorithms, and the community structure is more reasonable. It was verified that the algorithm can mine potential cooperative research teams in co-author network.
Highlights
Modern scientific research projects are becoming more and more complex and larger in scale, and their research and development often require multiple researchers to jointly complete [1]
Further comparing the communities with less than 1% members, the result is shown in Figure 4. ere are 5 in ILovain and only 2 in Louvain-LSCR, which shows that the Louvain-LSCR algorithm can merge small communities in time
In order to identify the core nodes in the network, an LSCR algorithm based on local information is proposed
Summary
Modern scientific research projects are becoming more and more complex and larger in scale, and their research and development often require multiple researchers to jointly complete [1]. In order to solve the problem of too many iterations and too many small communities in the Louvain algorithm stage 2, this paper combines the Louvain algorithm with the new core node recognition algorithm LSCR and proposes a new LouvainLSCR algorithm. (2) Aiming at the problem of too many iterations and too many small communities in the Louvain algorithm stage 2, a new community detection algorithm Louvain-LSCR is proposed, which integrates the core node recognition algorithm LSCR into the Louvain algorithm.
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