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FUCL mining technique for book recommender system in library service

机译：图书馆服务推荐书系统的FUCL挖掘技术

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Recommender systems are important tools in library websites that assists the user to find the appropriate books. With the rapid development of internet technologies and the number of books has varied which waste of time and difficulty for finding from library searching system. This research presents a book recommendation system for university libraries to support user interests which are related in the same topic and faculty. The main motive of this research is to develop the technique which recommends the most suitable books to users according to the faculty of the user profile with book category, and book loan or FUCL technique. This is based on the combined features of association rule mining. The results show that FUCL mining technique is suitable to apply for the recommender book tool in the library and has a higher accuracy value than other technique.
机译：推荐系统是图书馆网站中的重要工具，可帮助用户找到适当的书籍。随着互联网技术的飞速发展和书籍数量的变化，浪费了时间，从图书馆检索系统中查找困难。这项研究为大学图书馆提供了一种图书推荐系统，以支持与同一主题和教职员工相关的用户兴趣。这项研究的主要目的是开发一种技术，该技术根据具有图书类别的用户个人资料的能力，以及图书借阅或FUCL技术向用户推荐最适合的图书。这是基于关联规则挖掘的组合功能。结果表明，FUCL挖掘技术适用于图书馆推荐书工具，具有比其他技术更高的准确性。

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