Skip navigation

DSpace

機構典藏 DSpace 系統致力於保存各式數位資料(如:文字、圖片、PDF)並使其易於取用。

點此認識 DSpace
DSpace logo
English
中文
  • 瀏覽論文
    • 校院系所
    • 出版年
    • 作者
    • 標題
    • 關鍵字
    • 指導教授
  • 搜尋 TDR
  • 授權 Q&A
    • 我的頁面
    • 接受 E-mail 通知
    • 編輯個人資料
  1. NTU Theses and Dissertations Repository
  2. 電機資訊學院
  3. 資訊工程學系
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57227
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor許永真
dc.contributor.authorDaniel Silva Navarroen
dc.contributor.author辛丹尼zh_TW
dc.date.accessioned2021-06-16T06:38:31Z-
dc.date.available2019-08-01
dc.date.copyright2014-08-01
dc.date.issued2014
dc.date.submitted2014-07-30
dc.identifier.citation[1] Abowd, G. D, Atkeson, C. G, Hong, Jason, Long, Sue, Kooper, Rob, Pinkerton,
and Mike. Cyberguide: A mobile context-aware tour guide. Wireless networks, 3(5):421–433, 1997.
[2] Ahn, H, Kim, K.J, and H. I. Mobile advertisment recommender system using col-
laborative filtering. In Proceedings of the 2006 conference of the Korea Society of Management Information Systems, pages 709 – 715, 2006.

[3] Brown,Barry,Chalmers, andMatthew. Tourismandmobiletechnology. InECSCW
2003, pages 335–354. Springer, 2003.
[4] BurkeandRobin. Knowledge-basedrecommendersystems. Encyclopedia of library
and information systems, 69(Supplement 32):175–186, 2000.
[5] R. Burke. Hybrid recommender systems: survey and experiments., 2002.
[6] R. Burke. The adaptive Web, chapter Hybrid web recommender systems. Springer
Berlin/Heidelberg, 2007.
[7]Console,I.Torre,I.Lombardi,S.Gioria,andV.Surano.Personalizedandadaptive services on board a car: An application for tourist information, 2003.
[8] D and Buhalis. eTourism: Information Technology for strategic tourism manage-
ment,. Prentice Hall, 2003.
[9] Davidson and Gordon. The most precious resource in the word, June 2004.
[10] M. J. Eppler and J. Mengis. The concept of information overload: A review of literature from organization science,accounting,marketing,mis,andrelateddisciplines. The information society, 20(5):325–344, 2004.
[11] Frohlich and D. M. Requirements for photoware. In Proceedings of CSCW, New York, 2002.
[12] Z. Gantner, S. Rendle, C. Freudenthaler, and L. Schmidt-Thieme. Mymedialite: A free recommender system library. In Proceedings of the fifth ACM conference on Recommender systems, pages 305–308. ACM, 2011.
[13] D. Goldberg, D. Nichols, B. M. Oki, and D. Terry. Using collaborative filtering to weave an information tapestry. Communications of the ACM -Special issue on information filtering, 35(12):61 – 70, 1992.
[14] P. Gupta, A. Goel, J. Lin, A. Sharma, D. Wang, and R. Zadeh. Wtf: the who to follow service at twitter. In Proceedings of the 22nd international conference on World Wide Web, pages 505 – 514, 2013.
[15] B. J, C. K, and K. C. A survey of map-based mobile guides, 2005.
[16] Jacoby and Jacob. Perspectives on information overload. Journal of consumer re-search, 1:432–435, 1984.
[17] Jensen and Bill. Simplicity: The new competitive advantage in a world of more, better, faster. Da Capo Press, 2000.
[18] T.Q.JiangandW.Lu. Improvedslopeonealgorithmbasedontimeweight. Applied Mechanics and Materials, 347:2365–2368, 2013.
[19] B. JS, H. D, and K. C. Empirical analysis of predictive algorithms for collaborative filtering. In Proceedings of the 14th conference of uncertainty in artificial intelligence
[20] E.-y. Kang, H. Kim, and J. Cho. Personalization method for tourist point of interest
(poi) recommendation. In Knowledge-Based Intelligent Information and Engineering Systems, pages 392–400. Springer, 2006.
[21] S.Loh,F.Lorenzi,R.Salndata,and.L.D. Atourismrecommendationsystembased
oncollaborationandtextanalysis.,. Information Technology & Tourism,5:157–165,
2003.
[22] M and Crang. Knowing, tourism and the practices of vision. Routledge, London,
1999.
[23] Maclachlan, D. Lemire, and Anna. Slope one predictors for online rating-based
collaborative filtering, 2005.
[24] A. Maruyama, N. Shibata, Y. Murata, K. Yasumoto, and M. Ito. A personal tourism
navigation system to support traveling multiple destinations with time restrictions.
In Advanced Information Networking and Applications, 2004. AINA 2004. 18th In-
ternational Conference on, volume 2, pages 18–21. IEEE, 2004.
[25] Z. Mi and C. Xu. A recommendation algorithm combining clustering metho and
slope one scheme, 2012.
[26] Minnaert and Lynn. Social tourism as opportunity for unplanned learning and be-
havior change. Journal of Travel Research, 51(5):607–616, 2012.
[27] Mj and Pazzani. A framework for collaborative, content-based and demographic filtering. Artificial Intelligence review, 13:393 – 408, 1999.
[28] S. NS, B. M, C. NE, and H. T. I’m feeling loco: a location based context aware
recommendation system. In Proceedings of the 8th international symposium on
location-based services, 2011.
[29] Porage, D. N. Chin, and Asanga. Acquiring user preference for product customization. InProceedings of the 8th International Conference on User Modeling,London,
UK, 2001.
[30] P. Resnick and H. R. Varian. Recommender systems. Communications of the ACM, 40:56 – 58, 1997.
[31] S.SandW.H. Inteligentsystemsfortourism. Introduction. IEEE Inteligent Systems, 17:53 – 55, 2002.
[32] A. Scherp and S. Boll. Generic support for personalized mobile multimedia tourist
applications. In Multimedia 04: proceedings of the 12th annual ACM international
conference on multimedia, pages 178 – 179, NY, 2004.
[33] Schiaffino,Silvia,Amandi,andAnalía. Buildinganexperttravelagentasasoftware
agent. Expert Systems with Applications, 36(2):1291–1299, 2009.
[34] Z.Sun,N.Luo,andW.Kuang. Onereal-timepersonalizedrecommendationsystems
based on slope one algorithm. In Fuzzy Systems and Knowledge Discovery (FSKD),
2011 Eighth International Conference on, volume 3, pages 1826–1830. IEEE, 2011.
[35] U. Travel. Travel association, ”us travel”, May 2014.
[36] H.Y.andL.Bian. Abayesiannetworkandanalytic hierarchyprocessbasedperson-
alized recommendations for tourist attraction over the internet, 2009.
[37] M. Ye, P. Yin, W.-C. Lee, and D.-L. Lee. Exploiting geographical influence for
collaborative point-of-interest recommendation. In Proceedings of the 34th inter-
national ACM SIGIR conference on Research and development in Information Re-
trieval, pages 325–334. ACM, 2011.
[38] Y. Zheng and X. Xie. Learning travel recommendations from user-generated gps
traces. ACM Transactions on Intelligent Systems and Technology (TIST), 2(1):2,
2011.
[39] Y.Zheng,L.Zhang,Z.Ma, X.Xie,andW.-Y.Ma. Recommendingfriendsandloca-
tions based on individual location history. ACM Transactions on the Web (TWEB),
5(1):5, 2011.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/57227-
dc.description.abstractTraveling is a very important activity on human life; moreover, is a very profitable business all over the world. However, when people start planning their trips overseas, searching for information about places to visit, can be a very time consuming and misleading task. This research, aims to create the first module of a bigger e-tourism recommendation platform for Taiwan travelers. This initial module, will focus in Taipei pre-travel issues and it will recommends point of interest using a collaborative filtering approach.
To effectuate the recommendation, a modified version of slope one algorithm was utilized to predict the unavailable ratings on the dataset and mixed with the traditional CF prediction algorithm. This mixed algorithm showed a 10.19\% MAE improvement in comparison to the basic traditional collaborative filtering approach.
To effectuate the experiments for this recommendation system, the dataset is composed by the most popular 86 points of interest in Taipei. These point of interest were reviewed by 27 foreigners living in Taiwan.
en
dc.description.provenanceMade available in DSpace on 2021-06-16T06:38:31Z (GMT). No. of bitstreams: 1
ntu-103-R97922151-1.pdf: 4561323 bytes, checksum: b5ffb7d91d8e6476bad9c1e30c785b16 (MD5)
Previous issue date: 2014
en
dc.description.tableofcontentsAbstract v
1 Introduction 1
1.1 Motivation 1
1.1.1 Pre-Visiting Issues 2
1.1.2 In-Visiting Issues 3
1.1.3 Post-Visiting Issues 3
1.2 Objective 4
1.3 Thesis Organization 5
2 Related Work 7
2.1 Recommender Systems 7
2.2 Types of Recommender Systems 8
2.2.1 Demographic Recommendation 8
2.2.2 Content Based Filtering 8
2.2.3 Knowledge Based Filtering 9
2.2.4 Collaborative Filtering 10
2.2.5 Hybrid Recommender System 13
2.3 Tourism Recommender Systems 14
2.3.1 Travelers’ Issues 14
2.3.2 Popular Tourism Recommendation Services 15
3 Taipei Tourism Recommender System
17 3.1 Problem Definition 17
3.1.1 A Common Scenario 17
3.1.2 Objective 18
3.1.3 Definitions 18
3.2 The Recommender System 20
3.2.1 System Arquitecture 20
3.2.2 The Recommendation Algorithm 21
4 TP-REC Implementation 27
4.1 The Software 27
4.1.1 The Control Layer 28
4.1.2 The Model Layer 28
4.1.3 The View Layer 28
4.2 The User Interface 29
4.2.1 Login view 29
4.2.2 Main view 30
5 Experimentation And Evaluation 37
5.1 Data Collection And Data Presentation 37
5.1.1 Point Of Interest 38
5.1.2 Users’ Ratings and Background 38
5.2 Experiments And Performance Results 40
5.2.1 Experiments And Selected Benchmarking Algorithms 41
5.2.2 Experiments Results 42
5.3 Users’ Recommendation Feedback 43
5.3.1 The Interviewed Users 43
5.3.2 The Interview Methodology 44
5.3.3 Users’ Interview Results 45
5.3.4 Interviewee Conclusion Analysis 46
6 Conclusion and Future Work 47
6.1 Summary of Contributions 48
6.2 Limitations 48
6.3 Future Work 49
Bibliography 51
dc.language.isoen
dc.subject旅遊zh_TW
dc.subject旅遊導覽zh_TW
dc.subject推薦系統zh_TW
dc.subject?Recommender Systemen
dc.subjecte-tourismen
dc.subjecttourismen
dc.title協同過濾式推薦系統於特定文化背景之旅遊導覽zh_TW
dc.titleA collaborative filtering recommendation system for e-tourism from a specific cultural perspectiveen
dc.typeThesis
dc.date.schoolyear102-2
dc.description.degree碩士
dc.contributor.coadvisor紀婉容,蔡宗翰,林光龍
dc.subject.keyword推薦系統,旅遊導覽,旅遊,zh_TW
dc.subject.keyword?Recommender System,e-tourism,tourism,en
dc.relation.page55
dc.rights.note有償授權
dc.date.accepted2014-07-30
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

文件中的檔案:
檔案 大小格式 
ntu-103-1.pdf
  未授權公開取用
4.45 MBAdobe PDF
顯示文件簡單紀錄


系統中的文件,除了特別指名其著作權條款之外,均受到著作權保護,並且保留所有的權利。

社群連結
聯絡資訊
10617臺北市大安區羅斯福路四段1號
No.1 Sec.4, Roosevelt Rd., Taipei, Taiwan, R.O.C. 106
Tel: (02)33662353
Email: ntuetds@ntu.edu.tw
意見箱
相關連結
館藏目錄
國內圖書館整合查詢 MetaCat
臺大學術典藏 NTU Scholars
臺大圖書館數位典藏館
本站聲明
© NTU Library All Rights Reserved