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A Network Visualization Method Based on Hierarchical Community Structure

Author: TanZuo
Tutor: WangXiaoFan
School: Shanghai Jiaotong University
Course: Control Engineering
Keywords: Network Visualization Hierarchy Community Structure Force Directed Algorithm Circle Layout
CLC: TP391.41
Type: Master's thesis
Year: 2012
Downloads: 180
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Abstract


With the development of the complex network theory and the growth of the scale of the practical data, traditional methods can not satisfy the needs to analyze and manage the network data. To help users understand the network structure and extract the implicit information, network visualization technologies have been developing rapidly. This thesis proposes a network visualization method based on hierarchical community structure. We use the Blondel fast community method to divide network into multi‐level communities, then apply the force directed algorithm and the circle layout method to visualize the network in each community. Moreover, we introduce a threshold value to transit between these two layout methods. The main contributions of the thesis are summarized as follows:1. The thesis proposes a new visualization method based on hierarchical community structure, in which we first use the community algorithm based on modularity optimization to divide the network into hierarchical communities, then layout each community on all levels until we get the entire layout of the network;2. Within each community, we use both the force directed algorithm and the circle layout method. In addition, we modify the traditional FR algorithm through changing parameters, display areas, the effect scope of force and so on, to improve the force directed algorithm to be more suitable for dealing with the community structure; Meanwhile, we introduce the concept of edge density between communities which enables implementing circle layout on the local scale and transiting between the two layout methods through controlling an edge density related threshold value.3. The thesis enumerates some of the most popular general visualization software, and compares the result by running our method with theirs on 3 different networks.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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