Table 8.

Cited reference concerned with acupuncture for cerebral infarction that details of knowledge clusters.

Cluster ID	Size	Silhouette	Mean (Year)	Label (LLR)	Label (MI)
0	41	0.819	2018	Visualization analysis	Ischemic stroke rehabilitation
1	30	0.847	2013	Cerebral ischemia	Ischemic stroke rehabilitation
2	25	0.881	2008	Novel avenue	Ischemic stroke rehabilitation
3	21	0.931	2008	Diabetes mellitu	Ischemic stroke rehabilitation
4	18	0.969	2018	Electro-acupuncture treatment	Ischemic stroke rehabilitation
5	18	0.944	2014	Neurotrophic factor	Ischemic stroke rehabilitation
6	17	0.928	2016	Therapeutic effect	Ischemic stroke rehabilitation
7	16	0.945	2007	Baihui acupoint	Ischemic brain injury
8	16	0.959	2011	Scopus-based literature analysis	Ischemic stroke rehabilitation
9	15	0.960	2017	Memory deficit	Spastic paresis
10	14	0.989	2020	Neuroinflammatory damage	Ischemic stroke rehabilitation
11	12	0.939	2013	Acute stroke	White matter microstructure
12	11	0.925	2013	Controlled trial	Cerebral ischemia
15	7	0.926	2012	Factorial design	Cerebral ischemia
16	6	0.943	2014	Population-based study	Cerebral ischemia

The cluster analysis results mainly include cluster ID, mean year, size, silhouette, label (LLR), and label (MI). Cluster ID is the number after clustering, and Size represents the number of members contained in the cluster. The larger the size is, the smaller the number. Mean Year represents the average year of the literature in the cluster, which can be used to judge the distance of the cited literature in the cluster. The larger the log-likelihood ratio (LLR) is, the more representative the cluster category; mutual information (MI) is mainly used to represent the relationship between terms and categories in text mining, and it does not consider the frequency of feature words.