應用資料探勘技術於旅遊景點推薦

文化大學機構典藏 CCUR > 商學院 > 資訊管理學系暨資訊管理研究所 > 博碩士論文 > Item 987654321/28449

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题名:	應用資料探勘技術於旅遊景點推薦 Applying Data Mining Techniques for Tourist Spot Recommendations
作者:	麥瑟莉 Indriana, Marcelli
贡献者:	資訊管理學系
关键词:	Hybrid Recommender System Data Mining Linear Regression Neural Network Content-Based Filtering Collaborative Filtering Demographic Filtering
日期:	2014-06
上传时间:	2014-10-07 16:17:54 (UTC+8)
摘要:	Recommender systems have become an important research area in past few years. They have been developed for a variety of domains, especially e-commerce. Recommender systems also can be applied in tourism industry to help tourists organizing their travel plans. Recommender systems can be developed by a variety of different techniques such as Content-Based filtering (CB), Collaborative Filtering (CF), and Demographic Filtering (DF). However, each method has its own advantages and disadvantages. For this reason, many previous researches used several mixed methods with an aim to reduce the disadvantages of using a single method and get more accurate recommendations. In this research, we proposed a hybrid recommender system that combines the results of different recommendation methods using data mining techniques. Data mining technique is a method to dig out hidden knowledge and rules among the various items from large number of information and establish the relationship between model data attributes and categories in order to get more effective relationship model predictions. The experimental results showed that the proposed hybrid recommendation method outperforms each individual recommendation method in terms of five evaluation metrics.
显示于类别:	[資訊管理學系暨資訊管理研究所 ] 博碩士論文

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