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論文中文名稱:結合情境資訊與適地性服務之餐廳推薦 [以論文名稱查詢館藏系統]
論文英文名稱:Integrate the Context Information and Location-based Service for Restaurant Recommendation [以論文名稱查詢館藏系統]
院校名稱:臺北科技大學
學院名稱:管理學院
系所名稱:資訊管理研究所
畢業學年度:102
出版年度:103
中文姓名:官思伍
英文姓名:Sz-Wu Guan
研究生學號:101938013
學位類別:碩士
語文別:中文
口試日期:2014-07-01
論文頁數:64
指導教授中文名:翁頌舜
指導教授英文名:Sung-Shun Weng
口試委員中文名:蕭瑞祥;吳瑞堯;楊欣哲
口試委員英文名:Ruey-Shiang Shaw;Rei-Yao Wu;Shin-Jer Yang
中文關鍵詞:情境感知推薦系統適地性服務Place of Interests
英文關鍵詞:Context-AwarenessRecommendation SystemsLocation-based ServicesPlace of Interests
論文中文摘要:透過智慧型手機可以隨時隨地上網、收發電子郵件或購物,使生活更加便利,同時,情境感知應用藉由智慧型手機輔助之下,發展更無可限量;手機內建許多感測器,可以用來取得使用者周遭情境資料,加以過濾之後,可以更準確掌握使用者情境資訊,視需求應用在不同作用上,情境資訊也可以改善推薦系統資料稀疏性問題。
利用手機擷取使用者地理座標,演算Place of Interests,也就是使用者經常出現之地理區域,給予新使用者餐廳推薦之參考,可解決推薦的冷啟動問題。本研究結合情境感知、適地性服務及推薦系統等概念,藉由手機端取得使用者餐廳評分及情境資訊,包含地理座標、時間、天氣、速度以及方向等;伺服器端負責使用者之Place of Interests運算:找出潛在地緣關係、推薦模組運算:結合內容導向與協同過濾推薦方法以及情境分類,使餐廳推薦結果符合使用者需求時之情境。
最終,在本研究推薦機制下,根據時間、天氣、速度、方向等情境修正,選擇Cosine 60度以下之相似使用者,預測誤差值約為0.5,在100位使用者實際使用後,給予本餐廳推薦App正面評價與建議,推薦結果符合使用者需求產生時之情境。
論文英文摘要:Due to the increasing of smartphone users, it becomes more convenient for people to surf on the net. In the meanwhile, more conveniences are found by combining the function of context awareness and the sensors which are equipped in the mobile phones. The sensors can catch users’ context data. After filtering and computing, it shows the users’ their contextual information. Context awareness can not only extract the context data, but also adapt to users’ using environment. In addition, since recommendation systems must face the increasing amounts of data, through the recommendation mechanism, we can find out the needed information easier.
The study stands on three concepts, context awareness, location-based service, and recommendation system. A mobile App of restaurant recommendation first collects users’ recommending requests, users’ context (users’ coordinates, time, weather, speed and directions) and their ratings of restaurants. Then, the server, therefore, contains the collection of users’ Place-of-Interests, recommending items and the contextual classification. As result, this system can assist users by providing their personalized Place-of-Interests and current context. Also, it finally enhances the result of the restaurant recommendation.
論文目次:中文摘要 I
英文摘要 II
誌 謝 III
目 錄 IV
表目錄 VI
圖目錄 VII
第一章 緒論 1
1.1 研究背景與動機 2
1.2 研究目的 5
1.3 論文架構 6
第二章 文獻探討 7
2.1 情境感知(CONTEXT-AWARENESS) 7
2.1.1 情境感知相關應用 10
2.2 PLACE OF INTERESTS 11
2.3 推薦系統 12
2.3.1 內容導向推薦(Content-based Recommendations) 13
2.3.2 協同過濾推薦(Collaborative Filtering Recommendations) 13
2.3.3 整合(Hybrid) 16
2.4 決策樹 17
2.5 利用情境、POI資訊之餐廳推薦 19
第三章 研究方法 20
3.1 系統架構 20
3.2 餐廳推薦流程 22
3.3 社群關係建立(利用POI資訊) 25
3.4 餐廳推薦模組(內容導向與協同過濾) 31
3.4.1 取得使用者輸入的資料 33
3.4.2 產生相似的使用者群或餐廳項目 36
3.4.3 產生推薦結果 38
3.5 依使用者情境分類(決策樹) 39
3.5.1 使用者情境 39
3.5.2 分類 40
第四章 實驗設計與結果 42
4.1 POI形成 43
4.2 餐廳推薦 45
4.3 情境分類 48
4.3.1 方向與速度調整推薦列表 48
4.3.2 情境決策樹調整推薦列表 49
4.3.3 不同情境之餐廳推薦列表 52
4.4 餐廳推薦APP評估 53
第五章 結論與未來展望 58
5.1 結論 58
5.2 研究限制與未來展望 59
參考文獻 60
附錄 64
系統評估問卷 64
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論文全文使用權限:同意授權於2017-08-07起公開