Recommender system for traveling abroad using data mining techniques
碩士 === 國立雲林科技大學 === 資訊管理系碩士班 === 95 === The improvement of information technology makes storage no longer problems. And the born of Internet make information transfer faster than ever. It brings us convenient life. But more and more information result in a new problem─Information Overload. Today, mu...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2007
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| Online Access: | http://ndltd.ncl.edu.tw/handle/85899742737585121676 |
| Summary: | 碩士 === 國立雲林科技大學 === 資訊管理系碩士班 === 95 === The improvement of information technology makes storage no longer problems. And the born of Internet make information transfer faster than ever. It brings us convenient life. But more and more information result in a new problem─Information Overload. Today, much more people are traveling abroad since they no longer have to work on weekends. Traveling abroad becomes a kind of trend. There are more than a hundred countries in the world. Many people would wonder which one fit me?
In our research, we try to use the three kind of recommender system technique to recommend customers which countries are the best location for you. In this way we can save a lot of time in hesitating where to go. In our research, we can find that hybrid recommender system is the best of the three according to the abroad records. Hence, it really can conquer the shortcomings of content-based filtering and collaborative filtering.
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