Research Article
Community Detection Based on Density Peak Clustering Model and Multiple Attribute Decision-Making Strategy TOPSIS
| | Input: , the network; , the keynodes of communities. | | | Output: , the partition of network. | | (1) | ; | | (2) | for in do | | (3) | if and then | | (4) | .add ; | | (5) | else | | (6) | .add ; | | (7) | end | | (8) | end | | (9) | arrange community frameworks in in the descending order of product of density and distance of nodes in the framework; | | (10) | for in do | | (11) | ’s first- and second-order neighbors; | | (12) | = calculate the four similarities between and ; | | (13) | while True do | | (14) | -similarity = TOPSIS ; | | (15) | node with max -similarity; | | (16) | c.add ; | | (17) | ifthen | | (18) | add ’s first- and second-order neighbors to ; | | (19) | update ; | | (20) | else | | (21) | .remove ; | | (22) | break; | | (23) | end | | (24) | end | | (25) | end | | (26) | return |
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