請用此 Handle URI 來引用此文件：
http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/9108完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 許永真(Yung-Jen Hsu) | |
| dc.contributor.author | Hsiao-Wei Chen | en |
| dc.contributor.author | 陳筱薇 | zh_TW |
| dc.date.accessioned | 2021-05-20T20:09:29Z | - |
| dc.date.available | 2009-08-12 | |
| dc.date.available | 2021-05-20T20:09:29Z | - |
| dc.date.copyright | 2009-08-12 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-07-30 | |
| dc.identifier.citation | Bibliography
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UbiComp. [11] H. Chen, T. Finin, and A. Joshi. A context broker for building smart meeting rooms. In C. Schlenoff and M. Uschold, editors, Proceedings of the Knowledge Representation and Ontology for Autonomous Systems Symposium, 2004 AAAI Spring Symposium, pages 53–60, Stanford, California, March 2004. AAAI, AAAI Press, Menlo Park, CA. [12] H. Chen, T. Finin, and A. Joshi. Ontologies for Agents: Theory and Experiences, chapter The SOUPA Ontology for Pervasive Computing, pages 233–258. Whitestein Series in Software Agent Technologies. Springer, July 2005. [13] H. Chen, F. Perich, T. Finin, and A. Joshi. SOUPA: Standard ontology for ubiquitous and pervasive applications. In First Annual International Conference on Mobile and Ubiquitous Systems: Networking and Services (MobiQuitous’04), pages 258–267, August 2004. [14] K. Cheverst, N. Davies, K. Mitchell, A. Friday, and C. Efstratiou. Developing a contextaware electronic tourist guide: Some issues and experiences. 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A framework for collaborative, content-based and demographic filtering. Artificial Intelligence Review, 13:393–408, 1999. [27] C. Pils, I. Roussaki, andM. Strimpakou. Location-Based Context Retrieval and Filtering. 2006. [28] S. Poslad, H. Laamanen, M. Rainer, N. Achim, B. Phil, and Z. Alexander. Crumpet: Creation of user- friendly mobile services personalised for tourism, 2001. [29] E. Rich. User modeling via stereotypes, January 1979. [30] N. M. Sadeh, F. L. Gandon, and O. B. Kwon. Ambient intelligence: The MyCampus experience. Technical Report CMU-ISRI-05-123, School of Computer Science, Carnegie Mellon University, July 2005. [31] B. Sarwar, G. Karypis, J. Konstan, and J. Reidl. Item-based collaborative filtering recommendation algorithms. In Proceedings of the 10th international conference on World Wide Web, pages 285–295, New York, NY, USA, 2001. ACM. [32] B. Sarwar, G. Karypis, J. Konstan, and J. Riedl. Analysis of recommendation algorithms for e-commerce. 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There is more to context than location. Computers and Graphics, 23(6):893–901, 1999. [38] I. Schwab and W. Pohl. Learning information interest from positive examples, 1999. modifed mechine learning. [39] M. v. Setten. Experiments with a recommendation technique that learns category interests. In ICWI, pages 722–725, 2002. [40] M. v. Setten, S. Pokraev, and J.Koolwaaij. Context-aware recommendations in themobile tourist application compass. volume 3137, pages 235–244. Springer Berlin / Heidelberg, 2004. [41] Y. Takeuchi and M. Sugimoto. A user-adaptive city guide system with an unobtrusive navigation interface. Personal and Ubiquitous Computing, October 2007. [42] R. Want, A. Hopper, V. F. ao, and J. Gibbons. The active badge location system. ACM Transactions on Information Systems (TOIS), 10(1):91–102, January 1992. [43] J. Ye, L. Coyle, S. Dobson, and P. Nixon. A unified semantics space model. In J. Hightower, B. Schiele, and T. Strang, editors, LoCA, Lecture Notes in Computer Science, pages 103–120. Springer, 2007. [44] U. L. Yuhana, L.-l. Chen, J. Y.-j. Hsu, and W.-r. Jih. An ontology based approach for searching neighborhood building. In Proceedings of The Third International Seminar Information and Communication Technology Seminar (ICTS07), pages 106 – 112, Surabaya, Indonesia, September 11 2007. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/9108 | - |
| dc.description.abstract | 情境感知校園景點推薦系統根據參觀者的基本資料、參觀的行為、環境中的資訊(時間、天氣)以及景點間的相互關係，動態地推薦景點。
傳統景點推薦系統只考慮使用者偏好以及景點資訊，並沒有將情境的變化納入考量。此外，本系統針對新的使用者(new user)做推薦，在行程開始之前，系統並不假設擁有使用者過去的旅遊偏好資訊。 在使用者遊玩的過程中，系統觀察使用者與系統的互動，參考使用者對拜訪過的景點的喜好度，同時察覺作用中環境的變化，適時產生景點推薦。換句話說，本論文所提出的情境感知景點推薦系統，其需求和推薦系統不同，傳統產品推薦系統，會有一段冷開機(cold-start)的時間，這類推薦系統的品質要隨著對使用者的了解而增加，也就是說，它們必須累積了大量使用者的歷史交易紀錄後，才能得到有品質保證的推薦。但是本景點推薦系統，力求能在裋時間內察覺使用者偏好，推薦環境中使用者有興趣的景點，即便這個使用者是第一次使用本系統。 本系統包含三個主要技術：知識的具體化、情境感知、動態推薦。 知識的具體化使用本體論(Ontology)在特定應用領域表達一些概念的集合。本論文分別建立了時間和空間的知識庫。空間本體論用來架構景點在地理空間上的概念，例如：傅鐘是一個景點，椰林大道是一條路，傅鐘在椰林大道上是一個知識。在時間本體論上，根據本體論以節點為主的建構概念，使具體化的功能得以從初步資料推論高階的資訊。例如：九點是一個時間標記(time stamp)，透過推論讓電腦知道，九點在早上而且屬於吃飯的時間。 情境感知(context-aware)處理環境因子的變化，例如：使用者所在地、時間、天氣等資訊。 本推薦系統根據使用者的基本資料、同伴、因應現在的時間、天氣的變化，動態調整推薦的內容。 本論文實作了二個階段的實驗：第一階段在台大杜鵑花節我們邀請民眾考慮時間、天氣、以及與誰一同來玩等因素，為校園景點打分數。透過此活動收集到93筆移動軌跡，949筆景點喜好紀錄，以此建立使用者導向地理模型(user-based location model)，強化原有的景點模型做為推薦的基礎知識。在此地理模型中除了紀錄景點基本資料%(例如：編號、名稱、位置、類別、開放時間...) 還包括從分析民眾在台大遊玩的移動軌跡，發現的景點之間的關係(例如：我們觀察到很多人看完傅鐘接下來就會去總圖，因此這二個景點之間產生'下一站'的關係，即傅鐘的下一站是總圖)。 第二階段讓使用者帶著本推薦系統實際走訪校園，評估本系統的接受度、實用性。實驗進行方式，系統同時交錯列出二個推薦的景點列表，其中一個是有將情境的變化納入考慮，另一個則無，而使用者並不知道它們的差別。 我們紀錄十位使用者對推薦結果的反應(接受、拒絕、目前沒意見)，以此評估情境因子對景點推薦的助益。 | zh_TW |
| dc.description.abstract | In this paper, we propose a context-aware campus spots recommender system which detects the changes in the environment, and provides a list of spots to user whose preference cannot be retrieved at the trip beginning, on the basis of user’s responses of what had visited in the trip, what time it is, whether it rains, who company with the visitor, and attractions information. The traditional recommender systems overlooked that a decison making differs in different context (location, time, or weather). In order to get high quality recommendations, in the general recommender system user has to rate a sufficient number of items; However, this system learns user’s preferences during the trip and recommends spots that user are interested in, even if this is his first time contact with the system.
The system uses three main technologies: knowledge conceptualization, contextawareness ability, dynamic recommneder algorithm. Ontology is used to represent a set of concepts within the tourist domain. A spatial ontology organize spots information, and conceptualize geographic knowledge of NTU campus, such as Fu Bell is a spot, Royal Palm Blvd. is a road, and Fu Bell is on Royal Palm Blvd. is a geographic knowledge. The temporal concepts are built in ontology which could infer high-level information with the raw data. For example, 9:00 AMis a time stamp, by inference the system obtain that 9:00 AM is in the Morning and it belongs to eating time. Contextawareness ability copes with the changes in the enviroment. In short, the visitors could experience recommendations depending on their personal data and the environment conditions. With up-to-date user’s responses in the trip, the system dynamicly provides recommendations which vary with different time and weather condtion. | en |
| dc.description.provenance | Made available in DSpace on 2021-05-20T20:09:29Z (GMT). No. of bitstreams: 1 ntu-98-R96922020-1.pdf: 1483534 bytes, checksum: e6d5ac59fbca1422ee4908a3be50776f (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | Acknowledgments iii
Abstract v List of Figures xii List of Tables xiii Chapter 1 Introduction 1 1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 General Background Information . . . . . . . . . . . . . . . . . . . . 2 1.2.1 Recommender System . . . . . . . . . . . . . . . . . . . . . 2 1.2.2 Context-Aware Computing . . . . . . . . . . . . . . . . . . . 3 1.3 Context-Aware Spot Recommender System . . . . . . . . . . . . . . 3 1.3.1 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.3.2 System Archetecture . . . . . . . . . . . . . . . . . . . . . . 4 1.4 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 Chapter 2 Background and RelatedWork 7 2.1 Recommender System . . . . . . . . . . . . . . . . . . . . . . . . . 8 2.1.1 Content-Based Recommendation . . . . . . . . . . . . . . . . 9 2.1.2 Collaborative Filtering Recommendation . . . . . . . . . . . 10 2.1.3 Hybrid Approaches . . . . . . . . . . . . . . . . . . . . . . . 13 2.2 User Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.3 Context-Aware Computing . . . . . . . . . . . . . . . . . . . . . . . 17 2.3.1 Context-Aware Technology in Tourist Domain . . . . . . . . 18 2.3.2 Context-Aware Recommender System . . . . . . . . . . . . . 20 2.4 Ontology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Chapter 3 Context-Aware Campus Scenic Spots Recommender 25 3.1 Problem Formulation . . . . . . . . . . . . . . . . . . . . . . . . . . 26 3.2 Challenge and Proposed Solution . . . . . . . . . . . . . . . . . . . . 27 3.2.1 Data Collection and Analysis . . . . . . . . . . . . . . . . . . 28 3.2.2 POI Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.2.3 User Model . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 3.2.4 Context Model . . . . . . . . . . . . . . . . . . . . . . . . . 42 3.2.5 Context-Aware Recommendation Generation . . . . . . . . . 44 Chapter 4 Implementation and Evaluations 55 4.1 Scenario for Existing System . . . . . . . . . . . . . . . . . . . . . . 55 4.2 Experiment Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 59 4.2.1 Experiment Design . . . . . . . . . . . . . . . . . . . . . . . 60 4.2.2 Evaluation Metrics . . . . . . . . . . . . . . . . . . . . . . . 60 Chapter 5 Conclusion 65 Bibliography 68 xi | |
| dc.language.iso | en | |
| dc.title | 以本體論為基礎之情境感知校園景點推薦系統 | zh_TW |
| dc.title | An Ontology-based Context-aware Recommender System for Campus Scenic Spots | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 97-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 朱浩華(Hao-Hua Chu),王傑智(Chieh-Chih Wang) | |
| dc.subject.keyword | 情境感知,推薦系統,本體論, | zh_TW |
| dc.subject.keyword | Context-aware computing,recommender systems,multidimensional recommender systems,collaborative filtering,rating estimation,ontology,user modeling agent,location profiles, | en |
| dc.relation.page | 72 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2009-07-30 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 資訊工程學研究所 | zh_TW |
| 顯示於系所單位： | 資訊工程學系 | |
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