This research was supported by the National Natural Science Foundation of China under Grant No.61906089;the Aerospace Power Funds of China under Grant No.6141B09050342;the Fundamental Research Funds for the Central Universities of China under Grant No.NE2019104;the Jiangsu Foundation under Grant No.BK20190408.
In multi-label learning,it is rather expensive to label instances since they are simultaneously associated with multiple labels.Therefore,active learning,which reduces the labeling cost by actively querying the labels...
Supported by:This work was partially supported by the National Natural Science Foundation of China under Grant Nos.61773208 and 61906090;the Natural Science Foundation of Jiangsu Province of China under Grant Nos.BK20191287 and BK20170809.
Multi-label learning deals with the problem where each instance is associated with a set of class labels.In multilabel learning,different labels may have their own inherent characteristics for distinguishing each othe...
supported by the Fundamental Research Funds for the Central Universities of China;the National Natural Science Foundation of China under Grant No. 60905029;the Natural Science Foundation of Beijing of China under Grant No. 4112046
In this paper, we propose a balanced multi-label propagation algorithm (BMLPA) for overlapping community detection in social networks. As well as its fast speed, another important advantage of our method is good sta...