基於社群行為分析之階層化角色分類法

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姓名

郭依羚(Yi-ling Kuo) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

基於社群行為分析之階層化角色分類法
(Hierarchical Role Classification based on Social Behavior Analysis)

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摘要(中)

社群網路分析是一種透過資訊技術來對映及測量個人、群體、組織等不同群體的方法，它能利用社交資訊或社交行為之收集，來分析出不同情境下之社群關係，近年來已經有許多人投入社群網路分析的行列。其中，以社群偵測和發現為較熱門的領域，它能找出隱藏的社群用以輔佐推薦系統。
但是我們發現很少研究提到以階層化的方式去探討對抽象化社群的影響，因此，本篇論文的目的是設計一個藉由自動化產生的文章類別階層結合使用者有興趣之文章的角色分類分法。由實驗結果顯示，我們所提出的方法確實可以藉由階層化的方式提升分類的正確性。

摘要(英)

Social network analysis is a methodology to collect, analyze, and display the community relationship under different scenarios, it utilizes varied techniques to measure the social information, user-generated content, and social interaction. The last few years have seen a great deal of work on social network analysis. Community detection and discovery particularly is the most popular filed, and it can find the hidden communities to further analysis, such as community recommendation. However, role identification is a difficult job for many social network applications. One of the difficulties is to maintain and utilize large amount of distinct roles. And we found that there are few studies of any kind have examined the influence of using concept hierarchy to social network abstraction. In this paper, we attempt to adapt fuzzy classification method and construct a hierarchy for role classification, in other words, we want to design a role classification methodology based on the documents which users are interested in, and attempts to form the role hierarchy automatically then analyzes it. We believe this approach can encourage the utilization of social roles by considering their identifiable features at different levels.

關鍵字(中)

★ 模糊集合理論
★ 社群偵測
★ 文件分類
★ 社群網路分析

關鍵字(英)

★ Fuzzy Set Theory
★ Community Detection
★ Document Classification
★ Social Network Analysis

論文目次

Chinese Abstract i
English Abstrac ii
Acknowledgment iii
Table of Contents iv
List of Figures vi
List of Tables vii
Chapter 1 Introduction 1
1-1 Motivation 1
1-2 Contribution 4
Chapter 2 Related Work 6
Chapter 3 System Architecture 11
Chapter 4 Methodology 14
4-1 Deep community 15
A. Social behavior classification based on fuzzy classification model 16
B. Concept hierarchy of category 18
C. Abstract community 20
Chapter 5 Experiment 23
5-1 Experimental data sets 23
5-2 Cosine similarity 24
5-3 SVM 25
5-4 Results and discussions 25
Chapter 6 Conclusion 34
Reference 35

參考文獻

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指導教授

蔡孟峰(Meng-feng Tsai)

審核日期

2010-8-27

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