SAG Cluster: An unsupervised graph clustering based on collaborative similarity for community detection in complex networks
Many real-world social networks such as brain graph, protein structure, food web,
transportation system, World Wide Web, online social networks exist in the form of a complex …
transportation system, World Wide Web, online social networks exist in the form of a complex …
Clustering algorithm for community detection in complex network: a comprehensive review
Many real-world social networks exist in the form of a complex network, which includes very
large scale networks with structured or unstructured data and a set of graphs. This complex …
large scale networks with structured or unstructured data and a set of graphs. This complex …
Social voting advice applications—definitions, challenges, datasets and evaluation
Voting advice applications (VAAs) are online tools that have become increasingly popular
and purportedly aid users in deciding which party/candidate to vote for during an election. In …
and purportedly aid users in deciding which party/candidate to vote for during an election. In …
Exploring and analyzing the tor hidden services graph
The exploration and analysis of Web graphs has flourished in the recent past, producing a
large number of relevant and interesting research results. However, the unique …
large number of relevant and interesting research results. However, the unique …
Seed-centric approaches for community detection in complex networks
R Kanawati - Social Computing and Social Media: 6th International …, 2014 - Springer
Seed-centric algorithms constitue an emerging trend in the hot area of community detection
in complex networks. The basic idea underlaying these approaches consists on identifying …
in complex networks. The basic idea underlaying these approaches consists on identifying …
Topical cohesion of communities on Twitter
Abstract Nowadays, Online Social Networks (OSN) are commonly used by groups of users
to communicate. Members of a family, colleagues, fans of a brand, political groups... There is …
to communicate. Members of a family, colleagues, fans of a brand, political groups... There is …
Efficient large graph pattern mining for big data in the cloud
CC Chen, KW Lee, CC Chang… - … Conference on Big …, 2013 - ieeexplore.ieee.org
Mining big graph data is an important problem in the graph mining research area. Although
cloud computing is effective at solving traditional algorithm problems, mining frequent …
cloud computing is effective at solving traditional algorithm problems, mining frequent …
Measures for topical cohesion of user communities on twitter
Nowadays, Online Social Networks (OSN) are commonly used by groups of users to
communicate. Members of a family, colleagues, fans of a brand, political groups: the …
communicate. Members of a family, colleagues, fans of a brand, political groups: the …
Topological and topical characterisation of Twitter user communities
Purpose Most of the existing literature on online social networks (OSNs) either focuses on
community detection in graphs without considering the topic of the messages exchanged, or …
community detection in graphs without considering the topic of the messages exchanged, or …
谱聚类在社团发现中的应用
彭静， 廖乐健， 翟英， 仇晶 - 北京理工大学学报自然版, 2016 - journal.bit.edu.cn
在分析谱聚类原理的基础上, 研究了其在社团发现中的应用, 提出了快速估计社团数量的新方法.
该方法通过计算和分析Laplacian 矩阵特征值的分布来估计社团的数量, 利用K-means …
该方法通过计算和分析Laplacian 矩阵特征值的分布来估计社团的数量, 利用K-means …