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研究生:陳冠仲
研究生(外文):Kuan-Chung Chen
論文名稱:建構一具可適性之網路電視節目推薦系統
論文名稱(外文):Constructing an Adaptive Recommendation Scheme in the Web-TV Environment
指導教授:鄧維光
指導教授(外文):Wei-Guang Teng
學位類別:碩士
校院名稱:國立成功大學
系所名稱:工程科學系碩博士班
學門:工程學門
學類:綜合工程學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:英文
論文頁數:52
中文關鍵詞:網路電視互動性個人化推薦系統
外文關鍵詞:Web-TVinteractivitypersonalizationrecommendation system
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隨著資訊技術近年來的快速演進,為了進一步地改善使用者在觀看電視節目時的感受,電視的個人化以及互動性已經成為兩大具挑戰性的議題;而每天有成千上萬的電視節目在不同頻道中進行播映,因此人們往往需要花很多的時間去尋找他們想要觀看的節目。為了改善這些問題,我們提出在網路電視的環境中建構一具可適性之推薦系統,向使用者做出適當的建議。具體來說,我們根據一些隱含的使用者資訊以及其所提供之明確資訊來估計使用者對於電視節目的喜好程度。此外,我們以此一具可適性的推薦方法發展出了一個系統雛型,並驗證了此系統的可行性。
With recent advances in information techniques, it is noted that personalization and
interactivity have become two main challenging issues to further improve user experiences in
watching TV. As there are thousands of TV programs broadcasted everyday, people may
spend much time in finding their desirable programs. In view of this, we focus on developing
a proper recommendation scheme in the Web-TV environment so that users can be
recommended with appropriate programs. Specifically, we propose to estimate user
preferences and ratings with both explicit and implicit information provided by users.
Moreover, a prototype system which utilizes the adaptive recommendation approach is
developed to illustrate the feasibility of the proposed scheme in this work.
Chapter 1 Introduction .................................1
1.1 Motivation and Overview of the Thesis.................................1
1.2 Contributions of the Thesis ..................................2
Chapter 2 Preliminaries.................................4
2.1 Common Recommendation Techniques.................................4
2.1.1 Content-based Techniques.................................4
2.1.2 Collaborative Filtering Techniques.................................7
2.2 Improvements of Recommendation Techniques.................................10
2.2.1 Hybrid Recommendation Approaches .................................10
2.2.2 A Single Unifying Recommendation Model .................................11
Chapter 3 An Adaptive Recommendation Scheme for
Web-TV .................................13
3.1 Improving User Experiences in Watching TV Programs .................................13
3.2 Use of Time Factors in a Recommendation System .................................17
3.3 A Scheme for Web-TV Recommendations .................................20
3.4 Examples of Estimating User Preferences and Ratings .................................23
Chapter 4 Prototyping and Evaluation of Proposed Web-TV
Recommendation Scheme .................................27
4.1 A Prototype of the Web-TV Recommendation Scheme .................................27
4.2 Examinations on the Design and Effectiveness of
Proposed Web-TV Recommendation System .................................30
Chapter 5 Conclusions and Future Works .................................35
Bibliography .................................37
Appendix A SUMI Questionnaire (in English) .................................45
Appendix B SUMI Questionnaire (in Chinese) .................................49
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