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首页> 外文会议>2010 International Conference on Technologies and Applications of Artificial Intelligence >An Intelligent Recommendation Model with a Case Study on u-Tour Taiwan of Historical Momuments and Cultural Heritage
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An Intelligent Recommendation Model with a Case Study on u-Tour Taiwan of Historical Momuments and Cultural Heritage

机译：以u-Tour台湾历史遗迹和文化遗产为例的智能推荐模型

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Although there are many recommendation systems in use, they all face various challenges including the integration of diverse source data, improvement of prediction precision and meeting the userȁ9;s satisfaction. In order to increase success rate of satisfied recommendations as well as the applications in different domain fields, we propose an Intelligent Recommendation Model and conduct a case study on the historical monuments and cultural heritage of u-Tour Taiwan to show the feasibility of our model. In this research we use a hybrid approach to combine effective techniques such as popularization-based, community filtering, demographic profiling, and expertise-based in accordance with the type of users and the amount of available data to adjust weight values. We also use association rules of data mining technique to find potential patterns in the web access log, while clustering is used to assign users into different groups suitable for them. The incremental approach of our method can calculate the ranking value of content to be more precise. Finally, Adobe Flex is used to present the recommendation result of Taiwanȁ9;s 300 years of rich historical monuments and cultural heritage that provides more effective and efficient user interaction with less effort. Making full use of the valuable digital information of historical sites with our model, we hope to revitalize contemporary cultural and historical meaning that can bring people a brighter future and colorful life.
机译：虽然使用了许多推荐系统，但它们都面临各种挑战，包括集成各种源数据的整合，提高预测精度并满足用户的满意度。为了提高满足建议的成功率以及不同领域的应用，我们提出了一个智能推荐模式，并开展了对U-Tour台湾历史古迹和文化遗产的案例研究，以表达了我们模型的可行性。在本研究中，我们使用混合方法来组合有效的技术，例如基于普及的社区过滤，人口分析以及基于用户的类型和可用数据量来调整权重值的数量。我们还使用数据挖掘技术关联规则在Web Access Log中找到潜在模式，而群集用于将用户分配给适合于它们的不同组。我们方法的增量方法可以计算内容的排名值更精确。最后，Adobe Flex用于展示台湾ȁ9的推荐结果300年的历史纪念碑和文化遗产，提供更有效和高效的用户互动与较少的努力。充分利用历史遗迹的宝贵数字信息与我们的模式，我们希望振兴当代的文化和历史意义，可以带来一个更光明的未来和丰富多彩的生活。

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