微型电脑应用

高校图书馆是进行学习和科研的重要环境,更是师生获取参考资源的重要渠道。目前,部分高校的图书书目检索功能还停留在传统的线性检索和仅靠关键字检索的层面上,隐藏在海量的借阅记录背后的潜在关联无法被发现,对借书者的需求无法进行预测。关联规则是从大量数据中挖掘有价值的数据之间的相关关系。拟用等价的关联规则在书目检索模块实现图书的个性化推荐,以便借书者在海量的图书资料中找到自己感兴趣的图书信息。

College library provides an important learning and research environment and is also an important channel that teachers and students can access reference resources. Currently, in some colleges and universities bibliographical retrieval function still remains in the traditional linear search and keyword search levels. The hidden massive borrowing records can not be found. Demand for the borrower can not be predicted. Association rules is to mine correlation between the valuable date from the massive data. In bibliographic retrieval module, this paper intends to use the equivalent of association rules to achieve a personalized book recommendation. So that borrowers find their own interest in the mass of book information materials.