隨著網路的蓬勃發展，各行各業提供給消費者的服務已經不能再一成不變，必須讓所有服務都線上化。並且在社群網路的興起，以及資料庫的應用上，配合這些種種跡象。本論文希望能找出消費者的消費習慣，並提出更進階的推薦服務，讓業者與消費者都能有雙贏的局面。
　　本論文主要針對旅行業者實作一套線上的旅遊網站推薦系統。除了有一般旅遊網站的功能：註冊、旅遊介紹、報名、查詢、管理……等等。並利用每位會員的旅遊紀錄，結合社群網路和資料庫搜尋的概念，提出一好友判斷公式，為每位會員定義他的好友關係。並用真實旅遊紀錄去驗證所提出的好友判斷公式是否準確。最後分析公式中最好的參數設定，並利用找出來的好友關係進行推薦旅程的功能，增加旅客參加的意願。

Due to the development of the network, each industry must be changed to provide services to consumers. All services have to be online service. And combined with social networks and database applications with these factors, this thesis hopes to understand the spending habits of consumers, and come up with better recommendation service. In this thesis system will provide industry and consumers, a win-win website system.
This thesis is focused on the travel industry, to design and implement an online travel website recommendation system. Not only the function of the general travel websites, also to calculate each member's travel record. Use the concept of social networks and databases, propose a relation function. This function can find the true friendship between each member. Finally, analyzing the true travel record and finding the friendship. And use the friendship to recommend travels.

[1] P. Adams, “The Real Life Social Network,” Voices That Matter Web Design Conference, San Francisco June 2010
[2] Apache, http://www.apache.org/
[3] H. Chen, A. Chen, “A music recommendation system based on music data grouping and user interests,” Proceedings of the tenth international conference on Information and knowledge management, October 05-10, 2001, Atlanta, Georgia, USA.
[4] S. Debnath, N. Ganguly, P. Mitra, “Feature weighting in content based recommendation system using social network analysis,” In: Proc. 17th Intl. Conf. on World Wide Web, pp. 1041--1042, Beijing, China (2008)
[5] DHTML, http://en.wikipedia.org/wiki/DHTML
[6] A. Felfernig, S. Gordea, D. Jannach, E. Teppan, M. Zanker, “A Short Survey of Recommendation Technologies in Travel and Tourism”, in OEGAI Journal, vol. 25, no. 7, Oesterreichische Gesellschaft fuer Artificial Intelligence, 2007, pp. 17–22.
[7] M. Fire, L. Tenenboim, O. Lesser, R. Puzis, L. Rokach, and Y. Elovici, “Link Prediction in Social Networks Using Computationally Efficient Topological Features,” IEEE The 3rd International Conference on Privacy, Security, Risk, and Trust, and IEEE The 3rd Conference on Social Computing, pp. 73-80, 2011.
[8] Á. García-Crespo, R. Colomo-Palacios, J. Gómez-Berbís, F. García-Sánchez , “SOLAR: Social Link Advanced Recommenda。tion System”, Future Generation Computer Systems Jour., 26 (3), 2010, pp. 374 - 380 .
[9] J. Golbeck and J. Hendler. Filmtrust “Movie recommendations using trust in web-based social networks.,” In Proceedings of the IEEE CCNC, 2006.
[10] A. Goyal, F. Bonchi, and L. V. S. Lakshmanan, “Learning Influence Probabilities in Social Networks,” In Proceedings of the third ACM international conference on Web search and data mining, pp. 241–250, 2010.
[11] I. Guy, "Personalized Recommendation of Social Software Items Based on Social Relations," presented at the RecSys'09, New. York, pp. 53-60, 2009.
[12] HTML, http://html.net/
[13] P. Hui, and S. Buchegger, “Groupthink and Peer Pressure: Social Influence in Online Social Network Groups,” International Conference on Advances in Social Network Analysis and Mining, pp. 53-59, 2009.
[14] P. Jaccard, "Étude comparative de la distribution florale dans une portion des Alpes et des Jura", Bulletin de la Société Vaudoise des Sciences Naturelles 37: 547–579.
[15] JavaScript, www.javascript
[16] P. Kazienko, K. Musiał, T. Kajdanowicz, "Multidimensional Social Network in the Social Recommender System", IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 2009, accepted for publication.
[17] I. Konstas, V. Stathopoulos, and J. M. Jose, “On social networks and collaborative recommendation,” SIGIR’09: Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, pp. 195–202, 2009.
[18] D. McDonald, “Recommending collaboration with social networks: a comparative evaluation,” In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems(Ft. Lauderdale, FL, 2003). ACM, New York, NY, 2003.
[19] B. Miller, I. Albert, S. Lam, J. Konstan, J. Riedl, "MovieLens Unplugged: Experiences with a Recommender System on Four Mobile Devices." In Proceedings of HCI 2003.
[20] R. Mukherjee, E. Sajja, and S. Sen, "A movie recommendation system - An application of voting theory in user modeling," User Modeling and User-Adapted Interaction, vol. 13, pp. 5-33, 2003.
[21] MySQL, http://www.mysql.com/
[22] F. Walter, S. Battiston , and F. Schweitzer, “A model of a trust-based recommendation system on a social network,” Auton Agent Multi-Agent Syst (2008) 16:57–74 DOI 10.1007/s10458-007-9021-x.
[23] PHP, http://www.php.net/
[24] PHP資料庫網頁讀取流程, http://businesswing.net/php/1-3/
[25] What Is Social Networking?, http://www.whatissocialnetworking.com/
[26] 五福旅遊, http://www.lifetour.com.tw/
[27] 可樂旅遊, http://www.colatour.com.tw/
[28] 易遊網, http://www.eztravel.com.tw/
[29] 社群網站簡述, http://sls.weco.net/CollectiveNote20/Social
[30] 旅遊玩, http://www.anyway.com.tw/
[31] 華泰旅遊, http://www.gloriatour.com.tw/
[32] 雄獅旅遊, http://www.liontravel.com/
[33] 燦星旅遊, http://www.startravel.com.tw/
[34] 鳳凰旅行社, http://www.phoenix.com.tw/