Open AccessJournal Article
Overview on label propagation algorithm and applications
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The theoretical study of label propagation algorithm was introduced, its characteristics were analysed and its applications in multimedia information processing, retrieval,otation, classification and community discovery, etc. were summarized.Abstract:
This article introduced the theoretical study of label propagation algorithm,analysed its characteristics and summarized its applications in multimedia information processing,retrieval,annotation,classification and community discovery,etc.Finally,this paper proposed the future prospects and the trends of developments of the LPA algorithm.read more
Citations
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Detect structural-connected communities based on BSCHEF in C-DBLP
TL;DR: Based on Structural Connection Hierarchical Exploration (BSCHE) algorithm is selected to partition nodes in C‐DBLP because of its O(n) time cost, fast enough to process massive data, and its novel physical meaning of similarity between nodes defined by structural connection and availability.
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How to Better Identify Venture Capital Network Communities: Exploration of A Semi-Supervised Community Detection Method
Hong Xiong,Ying Fan +1 more
TL;DR: It can be shown to some extent that the semi-supervised community detection results in the VC network are more accurate and reasonable.
Proceedings ArticleDOI
Research on Label Propagation Algorithms Based on Clustering Coefficient
Mengjie Wang,Yusheng Xu +1 more
TL;DR: The results show that the algorithm reduces the randomness of the label propagation algorithm, enhances the stability and accuracy of detection result, and its adjustable parameter make it possible to have a good quality of community division for various types of networks.
Proceedings ArticleDOI
P-WLPA algorithm research on parallel framework Spark
TL;DR: Weighted Label Propagation Algorithm with Probability Threshold (P-WLPA) with typical serial execution prototype is proposed to be applied in data classification and performance comparison demonstrates the feasibility and efficiency of the parallel P- WLPA algorithm implementation on Spark.
Journal ArticleDOI
An Effective Identification Technology for Online News Comment Spammers in Internet Media
TL;DR: The results show that the technology proposed in this paper involves a lower data cost but a better identification effect than some traditional technologies based on the supervised classifier.
References
More filters
Journal ArticleDOI
Detect structural-connected communities based on BSCHEF in C-DBLP
TL;DR: Based on Structural Connection Hierarchical Exploration (BSCHE) algorithm is selected to partition nodes in C‐DBLP because of its O(n) time cost, fast enough to process massive data, and its novel physical meaning of similarity between nodes defined by structural connection and availability.
Journal ArticleDOI
How to Better Identify Venture Capital Network Communities: Exploration of A Semi-Supervised Community Detection Method
Hong Xiong,Ying Fan +1 more
TL;DR: It can be shown to some extent that the semi-supervised community detection results in the VC network are more accurate and reasonable.
Proceedings ArticleDOI
Research on Label Propagation Algorithms Based on Clustering Coefficient
Mengjie Wang,Yusheng Xu +1 more
TL;DR: The results show that the algorithm reduces the randomness of the label propagation algorithm, enhances the stability and accuracy of detection result, and its adjustable parameter make it possible to have a good quality of community division for various types of networks.
Proceedings ArticleDOI
P-WLPA algorithm research on parallel framework Spark
TL;DR: Weighted Label Propagation Algorithm with Probability Threshold (P-WLPA) with typical serial execution prototype is proposed to be applied in data classification and performance comparison demonstrates the feasibility and efficiency of the parallel P- WLPA algorithm implementation on Spark.
Journal ArticleDOI
An Effective Identification Technology for Online News Comment Spammers in Internet Media
TL;DR: The results show that the technology proposed in this paper involves a lower data cost but a better identification effect than some traditional technologies based on the supervised classifier.