Urban Functional Area Recognition Based on Unbalanced Clustering

Table 1

Overview of experimental methods.

Programme	Characteristic	Method description
1	Single source data identification function area [4]	Use POI to identify urban functional areas through frequency density analysis.
2	Multi-source data without unbalanced clustering	POI and microblog check-in data are used for machine learning and natural language processing, respectively. Finally, data fusion is used to identify urban functional areas.
3	Multi-source data with unbalanced clustering	Firstly, unbalanced clustering is used for data multiplication, machine learning, and natural language processing, respectively, and finally data fusion is used to identify urban functional areas.