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研究生(外文):Yi-Jung Shen
論文名稱(外文):Integration of Cross-Platform Data for Recommending Travel Activities and Events
指導教授(外文):Chia-Chi Wu
口試委員(外文):Yi-Fei ChenChien-Hsiang Liao
外文關鍵詞:Recommendation SystemSocial MediaImage AnalysisCross-platform Integration
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社群媒體已在旅遊業中扮演重要的角色,在現今旅遊景點的規劃中,人們也傾向參考社交媒體中網紅或朋友所標註的景點。本研究以跨平台的角度出發,結合KKDAY、Google Map、Instagram等平台,透過分析圖片及商家資料,推薦旅遊活動和周圍餐廳。本研究採實驗設計法,共進行兩個實驗:實驗一確定向使用者推薦的子類別,實驗二搭配子類別活動附近合適的餐廳進行推薦。研究結果顯示,有62.5%的使用者對於被推薦到的組合給予高分的回饋。本研究所提出,基於照片的旅遊活動與事件推薦方法,能提供適合的旅遊建議,並讓多數使用者感到滿意。
Social media has played a crucial role in the tourism industry, and in the current planning of travel destinations, people tend to refer to the places tagged by influencers or friends on social media. This study takes a cross-platform approach, integrating platforms such as KKDAY, Google Maps, and Instagram to analyze images and business data, in order to provide recommendations for travel activities and nearby restaurants. The study adopts an experimental design method, consisting of two experiments: Experiment 1 to determine the subcategories to recommend to users, and Experiment 2 to find suitable restaurant near the subcategory activities for recommendations. The experiment results indicate that 62.5% of the users gave high scores to the recommended combinations, suggesting that the photo-based recommendation method proposed in this study can provide suitable tourism advice and satisfy most users.
摘要 i
Abstract ii
目次 iii
表目錄 v
圖目錄 vi
第一章 緒論 1
第一節 研究背景及動機 1
一、 研究背景 1
二、 研究動機 3
第二章 文獻探討 6
第一節 推薦系統 6
一、 基於內容的過濾 6
二、 協同過濾 7
第二節 推薦系統附加資訊 9
第三節 研究應用平台介紹 10
一、 KKDAY 10
二、 Google Map 11
第四節 API介紹 11
第三章 研究方法 14
第一節 第一階段方法 15
一、 數據蒐集與預處理 16
二、 推薦系統架構 19
第二節 第二階段方法 23
一、 數據蒐集與預處理 24
二、 餐廳排名選擇 28
第四章 實驗結果與討論 31
第一節 實驗設計 31
一、 Instagram使用者資料集 31
二、 KKDAY 活動與事件資料集 32
三、 Google Map 商家資料集 33
第二節 實驗結果 34
第五章 結論與建議 39
第一節 研究結論與討論 39
一、 研究發現 39
二、 管理意涵 39
第二節 研究限制與未來建議 40
一、 研究限制 40
二、 未來建議 40
參考文獻 42
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