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博碩士論文 etd-0802107-175029 詳細資訊
Title page for etd-0802107-175029
論文名稱
Title
相識網路與信任網路中搜尋績效之比較
The comparison of search performance in acquaintance networks and trust networks
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
50
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2007-07-24
繳交日期
Date of Submission
2007-08-02
關鍵字
Keywords
信任網路、耗損率、小世界搜尋、相識網路
trust network, attrition rate, small world search, acquaintance network
統計
Statistics
本論文已被瀏覽 5844 次,被下載 7
The thesis/dissertation has been browsed 5844 times, has been downloaded 7 times.
中文摘要
隨著知識密集時代的來臨,人們越來越少有足夠的知識、能力去解決日益模糊且複雜的問題。據研究顯示人們向他人求助的程度,比向其他資源如資料庫或文件資料求助的程度要多的多。於是如何在人絡(社會)網路中搜尋(專家、合作夥伴、伴侶等)成為一個重要的議題。因為這些社會網路既不是規則網路也不是隨機網路,而是介於之中的小世界網路,所以這類議題也稱為小世界搜尋。
目前較常被用於在小世界中的搜尋機制有單一屬性 (如best-connected)與多重屬性(如social-distance)的方法,然而這些研究多是在相識網路中進行。實際上在相識網路中搜尋常因為耗損率過高,導致搜尋中止,使得搜尋的成功率下降。另一方面,進來許多研究者提出建構、推導人與人之間互信的信任網路。因為信任網路中的關係比相識網路中的關係更接近我們認定的朋友關係,所以在信任網路中的耗損率應比相識網路的耗損率低。
本研究因此提出以信任網路取代相識網路進行搜尋,希望提昇搜尋過程的品質。本研究以實驗設計的方式來比較評估相識網路與信任網路之搜尋績效,我們提出了三個實驗來驗證。在第一個實驗中,我們驗證所採用social-distance搜尋策略的有效性;第二個實驗則比較相識網路與信任網路在沒有耗損率的情況下的搜尋績效;第三個實驗中,我們把耗損率的因素納入實驗中,檢驗在相同耗損率與不同耗損率中的搜尋成效。實驗結果顯示了使用信任網路取代相識網路進行搜尋在耗損率差至10%以上即可以提升搜尋的成功率,因此驗證本研究所提方法的適用性。
Abstract
A social network represents the interconnected relations among people. In a knowledge-intensive era as of now, people have less capability to resolve more ill-defined and complicated problems. Several researches indicate that under such a circumstance people are more likely to turn to other people through their social networks than to consult sources like databases and documents. Searching in social networks is therefore an essential issue. In addition, typical social networks are neither regular nor completely random ones, but instead, they are mixtures between these two, which are referred to as small worlds. Consequently, such an issue is also called the small world search.
Search mechanism in the small world can be classified into single-attribute approach (e.g. best connected) and multiple-attribute approach (e.g. social distance). Relevant research works, however, are mostly based on acquaintance networks. And one of the problems to search in acquaintance networks is its high attrition rate that hinders further search and results in low success rate. On the other hand, in recent years several researchers focus on the constitution and propagation of trust networks that represent the trustworthy relations among people. Since trust implies much closer to what we mean friends rather than acquaintance, we believe that the attrition rate in trust networks should be lower than in acquaintance networks.
Based on this belief, we propose to search in trust networks rather than acquaintance networks to enhance the quality of the search process. We design three experiments to compare the search performance in the trust networks and in the acquaintance networks. Experiment I is to examine the “social-distance” search strategy we adopt in the search. The second experiment evaluates the performance comparison without considering attrition. Finally, we consider the attrition rate and attrition rate difference for the comparison. The results show that as long as the attrition rate difference is beyond 10%, search in trust networks performs better than in acquaintance networks. It therefore justifies the feasibility of our proposed approach in gaining good search performance.
目次 Table of Contents
CHAPTER 1 Introduction 1
1.1 Overview 1
1.2 Objective of the research 3
1.3 Organization of the Thesis 3
CHAPTER 2 Literature Review 4
2.1 Social Network Analysis 4
2.2 Small World 6
2.3 Searching in Small World 8
2.3.1 Single-attribute search approach 8
2.3.2 Multiple-attribute search approach 11
2.4 Attrition rate 13
2.5 Trust Social Networks 15
CHAPTER 3 Proposed Approach 17
Step 1: Trust Network Constitution 18
Step 2: Attribute Hierarchy Formation 19
Step 3: Social Distance Calculation 20
CHAPTER 4 Experiments and Results 22
4.1 Experimental Design 22
4.2 Experiment I 24
4.3 Experiment II 25
4.4 Experiment III 26
CHAPTER 5 Conclusions 32
5.1 Concluding remarks 32
5.2 Limitations 33
5.3 Future work 33
REFERENCES 35
Appendix A: The topology of acquaintance network (86 users, 1204 links) 38
Appendix B: The topology of trust network (86 users, 830 links) 39
Appendix C: The results of acquaintance network at different attrition rates 40
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