TY - GEN
T1 - Motif iteration model for network representation
AU - Lv, Lintao
AU - Qin, Zengchang
AU - Wan, Tao
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - Social media mining has become one of the most popular research areas in Big Data with the explosion of social networking information from Facebook, Twitter, LinkedIn, Weibo and so on. Understanding and representing the structure of a social network is a key in social media mining. In this paper, we propose the Motif Iteration Model (MIM) to represent the structure of a social network. As the name suggested, the new model is based on iteration of basic network motifs. In order to better show the properties of the model, a heuristic and greedy algorithm called Vertex Reordering and Arranging (VRA) is proposed by studying the adjacency matrix of the three-vertex undirected network motifs. The algorithm is for mapping from the adjacency matrix of a network to a binary image, it shows a new perspective of network structure visualization. In summary, this model provides a useful approach towards building link between images and networks and offers a new way of representing the structure of a social network.
AB - Social media mining has become one of the most popular research areas in Big Data with the explosion of social networking information from Facebook, Twitter, LinkedIn, Weibo and so on. Understanding and representing the structure of a social network is a key in social media mining. In this paper, we propose the Motif Iteration Model (MIM) to represent the structure of a social network. As the name suggested, the new model is based on iteration of basic network motifs. In order to better show the properties of the model, a heuristic and greedy algorithm called Vertex Reordering and Arranging (VRA) is proposed by studying the adjacency matrix of the three-vertex undirected network motifs. The algorithm is for mapping from the adjacency matrix of a network to a binary image, it shows a new perspective of network structure visualization. In summary, this model provides a useful approach towards building link between images and networks and offers a new way of representing the structure of a social network.
KW - Motif iteration model (MIM)
KW - Vertex reordering and arranging (VRA)
UR - https://www.scopus.com/pages/publications/85035080961
U2 - 10.1007/978-3-319-70139-4_66
DO - 10.1007/978-3-319-70139-4_66
M3 - 会议稿件
AN - SCOPUS:85035080961
SN - 9783319701387
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 647
EP - 656
BT - Neural Information Processing - 24th International Conference, ICONIP 2017, Proceedings
A2 - Zhao, Dongbin
A2 - Li, Yuanqing
A2 - El-Alfy, El-Sayed M.
A2 - Liu, Derong
A2 - Xie, Shengli
PB - Springer Verlag
T2 - 24th International Conference on Neural Information Processing, ICONIP 2017
Y2 - 14 November 2017 through 18 November 2017
ER -