Finding Dense 2-clubs in an Undirected Graph

• Main Authors: Yu-Fen Tseng, 曾鈺棻
• Other Authors: 林承穎
• Format: Others
• Language: en_US
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/huy7xk

碩士 === 樹德科技大學 === 資訊工程系碩士班 === 104 === In social network analysis(SNA), identifying community or organizations in a network is a popular issue. In graph theory perspective, that is to find a dense structure in a graph. There are many kinds of dense structure. For instance, clique, k-clique and k-club. A 2-club can be considered as a friends-of- friends group. This structure plays an important role in SNA. Apart from finding large k-club or finding k-club faster, there are experiments show that a large 2- club is just a maximum degree vertex with its adjacent vertices, which is just a star graph. Therefore, we enhance its structure by introducing the concept of “small-world” to 2-club, which is a dense 2-club. In this paper, we use average clustering coefficient to evaluate whether the result 2-club of these algorithms is “small-world enough”. We also propose a two-phase heuristic algorithm “TRIM” to find a dense 2-club based on the heuristic algorithm DROP. The experiment results show that our heuristic algorithm can improve the structure of 2-club. Comparing the experiment results, the average clustering coefficient of TRIM is better than DROP.