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網絡資料分群方法的比較 = A Comparison of Commun...

國立高雄大學統計學研究所

網絡資料分群方法的比較 = A Comparison of Community Detection Methods on Networks

Record Type:	Language materials, printed : monographic
Paralel Title:	A Comparison of Community Detection Methods on Networks
Author:	翁碩妤,
Secondary Intellectual Responsibility:	國立高雄大學
Place of Publication:	[高雄市]
Published:	撰者;
Year of Publication:	2014[民103]
Description:	42面圖,表 : 30公分;
Subject:	網絡分群
Subject:	Community structure
Online resource:	http://handle.ncl.edu.tw/11296/ndltd/92097962243172697346
Notes:	104年10月31日公開
Notes:	參考書目：面33-34
Summary:	網絡是由一些點（node）與這些點之間的關係所構成，本文所考慮的型式為無方向性與無權重的平面圖。近年，網絡資料逐漸在各領域被應用，如網際網絡（Google搜尋、臉書等）、生物網絡（生態、食物網、蛋白質交互作用網絡、神經網絡等）、社會網絡（社交網絡等）等，因此網絡資料分析遂成為熱門發展的技術，其中網絡分群是一基本且漸於成熟的議題。本研究利用Kuo, Ho and Liu (2013)所提出的網絡表示法－因子模型，對觀察網絡進行類似重抽樣的方式獲得一個全新的分群概念與方法，接著使用數個知名的實際網絡進行分析，並與文獻中常被使用的方法作比較，發現我們的方法有不錯的分群效果。 A Network is sets of nodes joined together in pairs by lines. In this paper we study the type of network which is the non-directional and un-weighted network. A number of recent studies is being applied in various fields, such as Internet networks(Google Search, Facebook, etc.), Biological networks(ecology, food webs, protein-protein in-teraction networks, neural networks, etc.), Social networks(social networks, etc.) so that the network analysis techniques became popular development, which is a basic and gradually mature issues. In this study, Kuo, Ho, and Liu (2013) proposed the new network notation “ factor model” to obtain the network and the new method concept similar resampling for detecting such communities. We apply the method to several useful networks to analysis, at the same time, against a method often used in the liter-ature and found that our method has good clustering effect.

網絡資料分群方法的比較 = A Comparison of Community Detection Methods on Networks
翁, 碩妤

網絡資料分群方法的比較 = A Comparison of Community Detection Methods on Networks / 翁碩妤撰 - [高雄市] : 撰者, 2014[民103]. - 42面 ; 圖,表 ; 30公分.
104年10月31日公開參考書目：面33-34.
網絡分群Community structure

網絡資料分群方法的比較 = A Comparison of Community Detection Methods on Networks
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