摘要
针对数字图书馆中书目资源规模的增大导致对关联图书书目检索的时效性和准确性不好的问题,提出一种基于相似度标签索引和关联规则挖掘的数字图书馆中的关联书目检索推荐方法。计算数字图书馆中的关联图书书目的相似度标签信息参量,在相似度便签索引下进行图书检索的语义分析,在语义本体模型中通过关联规则挖掘实现对相似用户和相似书目的信息融合和协同推荐,提高了对数字图书馆的检索效能。仿真测试结果表明,该推荐方法相比于传统方法具有较高的推荐准确性。
Aiming at poor timeliness and low accuracy of association books bibliography retrieval caused by the increase ofbibliographic resources in digital library,a recommendation retrieval method of association bibliographic in the digital library isput forward,which is based on similarity label index and association rules mining.The similarity label information parameters ofcorrelation book bibliography in the digital library are calculated.Semantic analysis of book retrieval is conducted in combination with the similarity label index.The association rules mining is used to realize information fusion and collaborative recommendation of similar users and similar bibliography in the semantic ontology model,and improve the retrieval efficiency of digital library.The simulation test result show that the recommended method has higher accuracy,compared with the traditional methods.
作者
刘培明
骆新泉
LIU Peiming;LUO Xinquan(Library of Yangzhou Polytechnic Institute,Yangzhou 225007,China;Xuzhou Institute of Technology,Xuzhou 221008,China)
出处
《现代电子技术》
北大核心
2017年第14期72-74,共3页
Modern Electronics Technique
基金
国家自然科学基金(11347154)
关键词
数字图书馆
关联规则挖掘
信息融合
书目检索
digital library
association rule mining
information fusion
bibliography retrieval
