推薦技術的主要目的是協助人們從大量資料中發掘自己需要的，推薦系統協助我們過濾資訊，再呈現那些我們會感興趣的資訊供我們參考，隨著無線網路技術的發展以及手提裝置運算能力的增加，推薦系統也在這樣的環境下轉型。我們著重於行動點對點網路環境底下的旅遊推薦系統，此系統使用協同過濾演算法，目的是提供移動中的旅客即時的旅遊景點建議，我們讓系統使用者交換他們已拜訪景點的評分資料，整合這些資料並匯集其他旅客對景點的建議，以此進行推薦做為使用者拜訪下個景點時的參考。
　　我們提出了六種資料交換方式，這些資料交換方式在同質及異質的實驗環境下被測試。實驗結果顯示，我們提出的資料交換方式與以內容為主的推薦方式相較，有較佳的推薦命中率；與只使用當面交換的資料來做推薦的方法相比，我們的資料交換方法也有較好的表現。最後我們對所有資料交換方法進行評估比較，最佳的方法應該要能夠進行好的推薦，同時維持適中的資料交換量。

　　Recommendation techniques are developed to uncover users‘ real needs among large volume of information. Recommender systems help us filter information and present those similar to our tastes. As wireless technology develops and mobile devices become more and more powerful, new recommender systems appear to adapt to new implementation environment. We focus on travel recommender systems implemented in a mobile P2P environment using collaborative filtering recommendation algorithms which intend to provide real-time suggestions to travelers when they are on the move. Using the concept of incorporating other travelers‘ suggestions to the next attraction, we let users exchange their ratings toward visited attractions and use these ratings as a basis of recommendation.
　　We proposed six data exchange algorithms for travelers to exchange their ratings. The proposed methods were experimented in the homogeneous and heterogeneous environment. The experimental results show that the proposed data exchange methods have better recommendation hit ratio than content-based recommendation methods and better performance compared with other methods only using ratings of users when they meet face-to-face. Finally, all methods are compared and evaluated. An optimal method should be able to strike a balance between algorithm performance and the amount of data communication.

Table of Contents
CHAPTER 1 - Introduction ................................................................................................ 1
1.1 Background ............................................................................................................... 1
1.2 Motivation ................................................................................................................. 2
1.3 Thesis Organization .................................................................................................. 3
CHAPTER 2 - Literature Review ....................................................................................... 5
2.1 Recommender Systems ............................................................................................. 5
2.1.1 Content-based Recommendation Approach ...................................................... 6
2.1.2 Collaborative Filtering Recommendation Approach ......................................... 7
2.2 Travel Recommender Systems ................................................................................. 9
2.3 Mobile Recommendation ........................................................................................ 12
2.3.1 Mobile Ad Hoc Networks (MANETs) ............................................................ 14
2.3.2 Social Mobile Service ...................................................................................... 16
2.4 Distributed Recommendation ................................................................................. 19
CHAPTER 3 - Data Exchanging Methods ....................................................................... 22
3.1 The Methods ....................................................................................................... 22
3.2 An Illustrating Example ...................................................................................... 29
3.3 Recommendation Mechanisms ........................................................................... 39
CHAPTER 4 –Preliminary Experiments and Results ....................................................... 42
4.1 Simulation Model ................................................................................................... 42
4.2 Simulation Environment ......................................................................................... 44
4.3 Correlation-Thresholding and Best-N-Neighbors .................................................. 47
4.4 Preliminary Experiments for Limited Propagation ................................................. 49
4.4.1 Experimental Results ....................................................................................... 49
CHAPTER 5 – Simulation Results and Evaluations ........................................................ 57
5.1 Performance Metrics ............................................................................................... 57
5.2 Comparing Content-based and Unconditional Data Exchange Methods ............... 59
5.3 Homogeneous Simulation Environment ................................................................. 61
5.4 Heterogeneous Simulation Environment ................................................................ 67
5.4.1 Results and Evaluations of the Well-planned Users ........................................ 68
5.4.2 Results and Evaluations of the Mis-planned Users .......................................... 71
CHAPTER 6 – Conclusions.............................................................................................. 77
Reference…………… ...................................................................................................... 79

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