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姓名 戴瑋(Wei Tai)  查詢紙本館藏   畢業系所 資訊工程學系
論文名稱 應用社會化協同標籤於網路資源搜尋
(Applying Social Collaborative Tagging in Web Resource Search)
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摘要(中) 摘 要
網際網路的發展越來越蓬勃,對人們的生活型態產生了極大的影響,人們習慣利用網路來達到學習、溝通、分享的目的,而網際網路讓這一切變得更加方便與簡單,並因應大家的需求而發展出許多便利卻又互動性高的網際網路應用平台;早期人們利用各大入口網站所提供的空間,來架設屬於自己的個人網頁或是留言板,而現今人們選擇架設互動性更高的部落格 (Blog),來發表自己的想法或見解;早期人們會使用 “我的最愛” ,或是從一些入口網站推薦的網頁,來記錄或是選擇與自己喜好相近的網頁,而現今人們使用互動性更高的social bookmark服務網站,來記錄與分享自己喜好的網頁;早期人們會連上大英百科全書的網站來找尋他們所需要的知識,而現今人們會連上維基百科 (Wikipedia) 網站來找尋與分享許許多多的知識;相同的是這些轉變都讓人與人之間的互動性越來越高了,並引領群體智慧來帶動更高的互動性,本來使用網際網路只是單純的接收網頁上所提供的資訊,而這些轉變能讓使用網際網路的人彼此互動更加熱絡,更有利於網際網路上的知識分享與知識循環。在O’’Reilly與MediaLive的國際研討會中討論到這些重要、精彩,極受歡迎的網路新應用,突然有規律地出現,「Web 2.0」的概念從此開始產生。
在如此互動性高的網際網路當中,人們快速的分享彼此的知識與意見,隨著網際網路上的資料量更快速的增加,如何從龐大的資料量中找尋正確而有幫助的資料,變得更加重要;人們為了方便在網際網路上搜尋資訊與資源,發展了搜尋速度相當快的搜尋引擎,而這些搜尋引擎所能提供的,僅是在網際網路上利用關鍵字與字元,來進行比對與定位,回傳的搜尋結果往往有好幾百筆,而使用者還必須要這在相當多的搜尋結果當中,一筆一筆找尋自己真正想要的資源與資訊,這樣的過程大大降低了整體搜尋資源的效率,改善搜尋引擎的速度並沒有辦法改善這種現象;人類對於事物習慣是以意義及概念的方式來思考,我們希望在現今關鍵字的搜尋方法當中,讓使用者對搜尋結果賦予概念及意義,並記錄在搜尋結果的標籤 (Tag) 當中,社會化協同標籤 (Social Collaborative Tagging) 以群體智慧 (Collective Intelligence) 的方式,透過大眾分類法 (Folksonomy),讓往後的搜尋結果與使用者所下的關鍵字之間,可以擁有更多的關聯性與概念上的相同程度;經由這樣的方式改善搜尋的過程,讓搜尋的準確性增加,減少使用者過濾龐大搜尋結果的負擔,進而提高整體的搜尋效率。我們也希望透過我們的系統,改善標籤與標籤之間的關聯性,讓使用者們所產生的群體智慧能達到完善的應用,我們改善了標籤一字多義 (polysemy) 與多字一義 (synonymy) 的問題,進而希望推動知識分享與知識循環的理想。
關鍵字 : Web 2.0、標籤、社會化協同標籤、群體智慧、大眾分類法、一字多義、多字一義、知識分享、知識循環
摘要(英) Abstract
Now days, the evolution of internet affects the lifestyle of people who usually access internet. This people are used to achieve learning、communication、sharing by accessing internet. In fact, internet makes these more convenient and easier. And more and more convenient and high interaction websites are developed for the requirement of people. More people choose to set up personal blog than personal homepage for higher interaction. Social bookmark website and the Wikipedia are the same case. It brings more and more interaction between people to arise Collective Intelligence. It promotes Knowledge Sharing and Recycling. The concept of "Web 2.0" began with a conference brainstorming session between O’’Reilly and MediaLive International. The web was more important than ever, with exciting new applications and sites popping up with surprising regularity.
People share knowledge and comments so fast in this high interaction internet. How to search correct and helpful information and resource in internet becomes more and more important. Human is used to think by concepts and meanings. Therefore, we want apply the concepts and meanings in search results and record in tags. Social Collaborative Tagging guides Collective Intelligence by Folksonomy. It brings more relativity between search results and user’s keywords. We hope the search process will be improved and the search efficiency will be increased by this way. We also want to increase the relativity of tags for improve polysemy and synonymy problem to advance knowledge sharing and recycling.
Keyword:Web 2.0、Tag、Social Collaborative Tagging、Collective Intelligence、Folksonomy、polysemy 、 synonymy、Knowledge Sharing.
關鍵字(中) ★ Web 2.0
★ 搜尋
★ 網路資源搜尋
★ 標籤
★ 群體智慧
★ 大眾分類法
★ 社會化協同標籤
關鍵字(英) ★ Tag
★ Collaborative Tagging
★ Folksonomy
★ Search
★ Web2.0
★ Tagging
★ Social Collaborative Tagging
論文目次 Contents
摘 要 I
Abstract III
Contents V
List of Figures VII
List of Tables VIIII
Chapter 1 Introduction 1
1.1 What is the motivation of this research? 1
1.2 What kinds of problems to be solved? Domain & scope. 2
1.3 Why are the problems significant? Characteristics & challenges 4
1.4 Who will be interested in these problems? 4
1.5 How to solve the problems? Method & systems. 5
1.6 Contribution of our solutions? 6
Chapter 2 Related work 7
2.1 General description of the problems (domain & scope ) 7
2.1.1 Current research status & challenges 11
2.1.2 Various approaches of problem solving 17
2.2 List and describe all the possible approaches of problem solving 19
2.2.1 Academic research 19
2.2.2 Industrial products 20
2.3 Comparison of various approaches with our approach (SWOT analysis) 21
2.3.1 Strength, Weakness 21
2.3.2 Opportunity, Threat 25
Chapter 3 Method and solution 26
3.1 Methodology & theory 26
3.1.1 Definition, axiom, theorem 26
3.1.2 Problem modeling 32
3.1.3 Theorem proof 36
3.2 Algorithms 37
3.2.1 Procedure of problem solving 38
3.2.2 Complexity analysis 41
Chapter 4 System Implementation 42
4.1 Implementation environment 42
4.1.1 Hardware and software platforms 42
4.1.2 Implementation languages & tools 42
4.2 System architecture 42
4.2.1 High-level system design and analysis ( block diagrams ) 43
4.2.2 Low-level system design and analysis ( process, flow, database structure ) 45
4.3 System demo 46
4.3.1 User interface, execution results, print screens, etc. 46
4.4 Experience learned form the implementation 47
4.4.1 Difficulties and possible solutions 47
Chapter 5 Simulation and Discussion 48
5.1 Simulation design and setup 48
5.2 Qualitative evaluation ( 質化 ) 49
5.2.1 Questionnaire design and survey 49
5.2.2 Results and lesson learned ( observation & explanation, etc 49
5.3 Quantitative evaluation ( 量化 ) 52
5.3.1 Performance evaluation 52
5.3.1.1 Recalls & precision 53
5.3.2 Results and lesson learned ( experimental data analysis & explanation ) 54
Chapter 6 Conclusion and future Work 63
Reference 64
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指導教授 楊鎮華(Stephen J.H. Yang) 審核日期 2008-7-10
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