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研究生:陳佳駿
研究生(外文):Chen, Jiajun
論文名稱:結合層級分析法與圖像呈現之推薦模型建立
論文名稱(外文):Designing Recommendation Model With Analytic Hierarchy Process (AHP) and Image-based Presentations.
指導教授:曾俊元
指導教授(外文):Tseng, Chinyang
口試委員:汪志堅賴錦慧曾俊元
口試委員(外文):Wang, ChihchienLai, ChinhuiTseng, Chinyang
口試日期:2012-06-15
學位類別:碩士
校院名稱:國立臺北大學
系所名稱:資訊管理研究所
學門:電算機學門
學類:電算機一般學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:44
中文關鍵詞:層級分析法圖像輔助推薦模型購買意願
外文關鍵詞:AHPPair-wise factor comparisonImage-based presentationPurchase intentionBFRInstant feedback
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本研究為網路推薦系統建立在網頁平台時,以往過濾方式對於使用者需求仍不精確,影響使用者獲取推薦的正確性。為增進過濾方式,結合多種過去以臻成熟理論,加入層級分析法,建立推薦模型,並採用因素刪減方式加快運算速度。研究內容主要以學生為對象,以四種推薦方式為比較對象。本研究以T檢定檢測樣本中,使用者對四種推薦模型設計的滿意度,結果顯示,圖像輔助與成對比較確實有助於使用者獲得較精準推薦,與過去推薦模型設計相比,能有效提高推薦精確度。本研究之結果可助於產品需求調查,透過產品特性來調查使用者的需求比重,並讓使用者獲得更滿意的推薦。
High accuracy of market surveys is critical because it often determines the marketing directions and strategies of a company. However, most customers are not clear to know what they really need. For company, it is hard to design or sell the appropriate products to customers if they could realize their demand. This paper applies Analytic Hierarchy Process (AHP) and image-based presentation to questionnaire design to give users instant alternative feedback with what they really need. From user decision-making behavior aspect, humans tend to make a more accurate preference decision in pair-wise factor comparison with precisely scoring to every factor. Furthermore, image-based presentations allow humans to imagine and visualize their real preference, and thus increase the accuracy and reliability of recommendations. In brief, this model focuses on improving the products’ reliability, performing real-time analysis, and increasing the purchasing intention. To evaluate the reliability of the model, the sample results pass the following tests: Cronbach’s Alpha test and pearson test. We verify all hypotheses by descriptive statistics, and T-test values of sample results show that users agree the statements of questions
致謝 I
國立臺北大學一○○學年度第二學期學位論文提要 II
Abstract III
Table of Context V
List of Table VII
List of figure VIII
1. Introduction 1
2. Literature 3
2.1. AHP 3
2.2. Branch Freezing Rule 4
2.3. Image-based Presentation 5
2.4. Recommendation System 5
2.5. Satisfaction 6
3. Method 8
3.1. Hypothesis 8
3.2. System Design 9
3.2.1. Model establish 9
3.2.2. Model description 12
3.2.3. Calculating method 14
4. Results and Analysis 19
4.1. Descriptive Statistics of participants 19
4.2. Reliability tests of questionnaire part II results 19
4.3. Hypothesis testing 21
5. Conclusions 24
6. Reference 26
Appendix A: the four recommendation system 29
Appendix B: description of satisfaction questionnaire 41
簡歷 43
著作權聲明 44

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