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FUCL mining technique for book recommender system in library service

机译：图书馆服务中书籍推荐系统的FUCL挖掘技术

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摘要

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：推荐器系统是库网站中的重要工具，帮助用户找到相应的书籍。随着互联网技术的快速发展，书籍数量有所不同，浪费时间和难以从图书馆搜索系统的发现。本研究提出了一本关于大学图书馆的书推荐系统，以支持在同一主题和教师中相关的用户利益。本研究的主要动力是开发该技术，该技术将根据用户简介的能力为用户推荐最适合的书籍，以及书籍类别，以及书籍贷款或FUCL技术。这是基于关联规则挖掘的组合特征。结果表明，FUCL挖掘技术适用于图书馆中的推荐书工具，具有比其他技术更高的准确值。

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