¡@¡@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.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0811109-023332 |
| Date | 11 August 2009 |
| Creators | Weng, Ling-chao |
| Contributors | Fu-ren Lin, San-yih Hwang, Shih-chieh Hsu, Wan-shiou Yang |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0811109-023332 |
| Rights | campus_withheld, Copyright information available at source archive |
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