臺灣博碩士論文加值系統

隨著網路的發展，愈來愈多的旅遊者可以在網路上找到相當多的旅遊資訊，並且自己規劃行程。同時行動網路的普及也使得我們能夠及時獲得許多資訊，作出更好的決定。過去曾有許多旅遊推薦系統，透過使用者相似性和情境感知進行推薦，但是這些系統缺乏一個有組織的結構來進行推薦，因此本研究發展出一個旅遊推薦系統，透過旅遊的主題來進行推薦。我們使用本體論(Ontology)，將原先毫無關聯的景點產生關聯，建構出旅遊主題的本體模型；並且透過旅遊紀錄找出潛在的旅遊主題，計算使用者之間的相似性來進行推薦；最後使用情境感知來提升推薦的效果，我們考慮情境因素，根據不同的季節和距離等，選出符合使用者興趣之景點。
最後透過本研究所做的系統評估，其結果顯示本系統在系統品質、資訊品質都有不錯的表現；在服務品質方面，我們可以看到情境感知的功能，確實能夠根據使用者需求與興趣，提供令人滿意的景點推薦。使用者對於本系統的評價大致上是良好的，使用者也同意未來要查詢旅遊資訊時，會繼續使用此系統，藉此找出符合自己興趣的景點。

With the development of Internet, more and more travelers search for travel information on the Internet. The travelers could use those information to help them plan itinerary. Because of the universal mobile internet, we could get a variety of information immediately, and it helps us make decision better. There are many recommendation systems using context-aware and user-user similarity model, but these systems did not have an organizational structure.
In this study, we propose a travel recommendation system, providing recommendation based on travel topic. The system introduces ontology technology to discover the relationship between each tourist attractions, and build a travel topic model. It also aim to find potential travel topic from user’s travel histories. The system is context-aware which can perceive the context around the user. It will provide different recommendation results when the context changes. The season and distance context information is considered during the recommendation process.
The evaluation result shows that our system can provide high satisfaction. The system is sufficient to meet user’s requirement, and it is capable to provide the tourist attraction that user is interested.

中文摘要 i
Abstract ii
誌 謝 iii
目 錄 iv
圖索引 v
表索引 vi
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 4
第二章 文獻探討 6
第一節 推薦系統（Recommender Systems）6
第二節 情境感知（Context-awareness） 11
第三節 本體論 14
第三章 研究方法 19
第一節 本體論建構 19
第二節 系統架構 29
第四章 系統實作 42
第一節 APP設計概念 43
第二節 APP功能展示與介面設計 44
第三節 使用情境範例 49
第五章 系統評估 52
第一節 評估方法與實驗設計 52
第二節 評估結果 52
第六章 結論 62
第一節 結論 62
第二節 未來研究建議 63
參考文獻 64
附錄一 71

中文部份
資策會FIND2014(H2)/「2014臺灣消費者行動裝置暨APP使用行為研究調查報告」


原文部份
Jie Lu , DianshuangWu, Mingsong Mao,Wei Wang, Guangquan Zhang
. (2015). Recommender system application developments: A survey. Decision Support Systems, 74, 12–32.

Rajani Chulyadyo, Philippe Leray. ( 2014 ) . A personalized recommender system from probabilistic relational model and users’ preferences. Procedia Computer Science, 35. 1063 – 1072.

Yeran Sun, Hongchao Fan, Mohamed Bakillah, Alexander Zipf. (2015). Road-based travel recommendation using geo-tagged images, Computers, Environment and Urban Systems, 53. 110–122.

Ahmad Hawalah, Maria Fasli. (2014). Utilizing contextual ontological user profiles for personalized recommendations. Expert Systems with Applications, 41. 4777–4797.

Drazen Nadoveza , Dimitris Kiritsis. (2014). Ontology-based approach for context modeling in enterprise applications, Computers in Industry, 65. 1218–1231.

Káthia Marçal de Oliveira, Firas Bacha, Houda Mnasser, Mourad Abed. (2013). Transportation ontology definition and application for the content personalization of user interfaces, Expert Systems with Applications, 40. 3145–3159.

J. Bobadilla, F. Ortega, A. Hernando, A. Gutiérrez. (2013). Recommender systems survey. Knowledge-Based Systems, 46. 109–132.
P. Resnick, H.R. Varian. (1997). Recommender systems, Communications of the ACM, 40. 56–58.

K. Verbert, N. Manouselis, X. Ochoa, M. Wolpers, H. Drachsler, I. Bosnic, E. Duval. (2012). Context-aware recommender systems for learning: a survey and future challenges. IEEE Transactions on Learning Technologies, 5. 318–335.

Abdul Majid , Ling Chena, Hamid Turab Mirza , Ibrar Hussain , Gencai Chena s. (2015). A system for mining interesting tourist locations and travel sequences from public geo-tagged photo. Data & Knowledge Engineering, 95. 66–86.

Zhen xing Xu, Ling Chen n, Gencai Chen. (2015). Topic based context-aware travel recommendation method exploiting geotagged photos. Neuro computing, 155. 99–107.

Bill N. Schilit, Norman Adams, and Roy Want. (1993). Context-Aware Computing Applications. In Proceedings of the Workshop on Mobile Computing Systems and Applications.

Guanling Chen and David Kotz. (2000). A Survey of Context-Aware Mobile Computing Research. Dartmouth Computer Science Technical Report TR. 2000-381

William Noah Schilit. (1995). A System Architecture for Context-Aware Mobile Computing.
Luis Omar Colombo-Mendoza , Rafael Valencia-Garcia, Alejandro Rodriguez-Gonzalez ,Giner Alor-Hernandez, Jose Javier Samper-ZapaterRecomMetz. (2015). A context-aware knowledge-based mobile recommender system for movie showtimes. Expert Systems with Applications Volume. 1202–1222.

Hawazin Badawi , Abdulmotaleb El Saddik. (2015). Towards a Context-Aware Biofeedback Activity Recommendation Mobile Application for Healthy Lifestyle, Procedia Computer Science, 21. 382–389.

Chang-Shing Lee, Young-Chung Chang, Mei-Hui Wang. (2009). Ontological recommendation multi-agent for Tainan City travel. Expert Systems with Applications, 36. 6740–6753.

Thomas R. Gruber. (1993). A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition.

Malak Al-Hassan, Haiyan Lu, Jie Lu. (2015). A semantic enhanced hybrid recommendation approach: A case study of e-Government tourism service recommendation system. Decision Support Systems. 7297–109.

A.K. Dey, G.D. Abowd, D. Salber. (2001). A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications. Human- Computer Interaction, 16. 97–166.

T. Hung-Wen, S. Von-Wun. (2004). A personalized restaurant recommender agent for mobile e-service. IEEE International Conference on e-Technology, e-Commerce and e-Service. 259–262.

A. Pashtan, R. Blattler, A.H. Andi, P. Scheuermann. (2003). CATIS: a context-aware tourist information system. The 4th International Workshop of Mobile Computing, Rostock.

L. Martinez, R.M. Rodriguez, M. Espinilla. (2009). Reja: a georeferenced hybrid recommender system for restaurants. IEEE/WIC/ACM 2009 International Joint Conferences on Web Intelligence and Intelligent Agent Technologies. WI-IAT '09, IET 2009. 187–190.

J.P. Lucas, N. Luz, M.N.Moreno, R. Anacleto, A. Almeida Figueiredo, C.Martins. (2013). A hybrid recommendation approach for a tourism system. Expert Systems with Applications, 40. 3532–3550.

A. Moreno, A. Valls, D. Isern, L. Marin, J. Borràs. (2013) SigTur/E-destination: ontologybased personalized recommendation of tourism and leisure activities, Engineering Applications of Artificial Intelligence, 26. 633–651.

T. Ruotsalo, K. Haav, A. Stoyanov, S. Roche, E. Fani, R. Deliai, E. Mäkelä, T. Kauppinen, E. Hyvönen. (2013). SMARTMUSEUM: a mobile recommender system for the web of data. Web Semantics: Science, Services and Agents on the World Wide Web, 20. 50–67.

W.-S. Yang, S.-Y. Hwang. (2013). iTravel: a recommender system in mobile peer-to-peer environment. Journal of Systems and Software, 86. 12–20.

A. García-Crespo, J. Chamizo, I. Rivera, M.Mencke, R. Colomo-Palacios, J.M. Gómez- Berbís. (2009). SPETA: social pervasive e-tourism advisor. Telematics and Informatics, 26. 306–315.

S. Schiaffino, A. Amandi. (2009). Building an expert travel agent as a software agent. Expert Systems with Applications, 36. 1291–1299.

Gediminas Adomavicius, Alexander Tuzhilin. (2005) Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions. IEEE Transactions on Knowledge and Data Engineering vol. 17 no. 6.

Tho, Q. T., Hui, S. C., & Fong, A. C. M. (2006). Automatic fuzzy ontology generation for semantic web. IEEE Transactions on Knowledge and Data Engineering, 18-6. 842–856.

Francisco, G. S., Rodrigo, M. B., Leonardo, C., Jesualdo, T. F. B., & Dagoberto, C. N. (2006). An ontology-based intelligent system for recruitment. Expert Systems with Applications, 31. 2248–263.

M. Bazire, P. Brezillon. (2005). Understanding context before using it, in: A.K. Dey, Boicho Kokinov, D. Leake, R. Turner (Eds.). International Conference on Contexts. 29–40

P. Brezillon, J. Pomerol. (1993). Contextual knowledge sharing and cooperation in intelligent assistant systems. Le Travail Humain. 1–33.

C. Bettini, O. Brdiczka, K. Henricksen, J. Indulska, D. Nicklas, A. Ranganathan, D. Riboni. (2010). A survey of context modelling and reasoning techniques. Pervasive Mob. Comput, 6 (2). 161–180.

D. Ejigu, M. Scuturici, L. Brunie. (2007). An ontology-based approach to context modeling and reasoning in pervasive computing. Fifth Annual IEEE International Conference on Pervasive Computing and Communications Workshops. 14–19.

X.H. Wang, T. Gu, D.Q. Zhang, H.K. Pung. (2004). Ontology based context modeling and reasoning using OWL. IEEE Annual Conference on Pervasive Computing and Communications Workshops, Proceedings of the Second. 18–22.

Natalya F.Noy, Deborah L.McGuinness. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. Stanford University, Stanford, CA, 94305.

Femke Ongenae. (2013). A probabilistic ontology-based platform for self-learning context-aware healthcare applications. Expert System with Applications 407629-7646.

Michael C. Daconta, Leo J. Obrst, Kevin T. Smith. (2004). The Semantic Web: A guide to the future of XML, Web Services and Knowledge Management. Computing Reviews,45(12). 778-779.