基于《中国图书馆分类法》的高校图书馆书目推荐服务研究

摘要

In view of the fact that the library personalized recommendation service based on association rides is easy to produce redundant association rules and lose effective association rules, this paper proposes the university library bibliographic recommendation method based on the Chinese Library Classification. In the data preprocessing stage, the paper classifies the books in the original borrowing record in accordance with the Chinese Library Classification. Then the paper uses the Apriori algorithm to mine and produce the association rules, and expand the books into recommended books. Finally, an example proves that the nzles produced by this method is more universal than the rules produced by the existing recommendation method based on the books' names, and the recommendation results are expandable.%针对目前基于关联规则的图书馆个性化推荐服务易产生冗余关联规则和丢失有效关联规则的问题，提出了一种基于《中国图书馆分类法》的高校图书馆书目推荐方法。在数据预处理阶段，将原始借阅记录中的书目按照《中国图书馆分类法》进行分类整理，然后利用Apriori算法挖掘产生关联规则，并将其扩展为推荐书目，最后通过实例验证，该方法比现有基于书籍名称的推荐方法所产生的规则更具一般性，推荐结果具有可扩展性。