Research Article
A Local Extended Algorithm Combined with Degree and Clustering Coefficient to Optimize Overlapping Community Detection
Algorithm 2
Community merging and isolated nodes adjustment.
| | Input: local subgraph LC | | | Output: community detection results OC | | (1) | Community merging | | (2) | = calculateAvgOS(LC) | | (3) | OC = [] | | (4) | for i in LC do | | (5) | j = i + 1 | | (6) | for j in LC do | | (7) | ifthen | | (8) | OC.append(i j) | | (9) | end if | | (10) | end for | | (11) | end for | | (12) | Isolated nodes adjustment | | (13) | for i in OC do | | (14) | if len(i) = = 0 and otherSide(i[0]) then | | (15) | = i[0] | | (16) | neighbors[] = findeNeighbors() | | (17) | | | (18) | for in neighbors[] do | | (19) | ifthen | | (20) | addIsolateNode(, ,OC) | | (21) | end if | | (22) | end for | | (23) | end if | | (24) | end for |
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