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作 者:马丽[1] Ma Li(Library,Xi’an Medical University,Xi’an 710021,China)
出 处:《江苏科技信息》2022年第30期57-59,共3页Jiangsu Science and Technology Information
摘 要:为提高地方公共图书馆数据库中信息资源的查全率,文章引进了关联规则挖掘技术,设计了一种针对图书馆信息资源的全新整合方法。为确保构建的模型与资源分布具有较强的适配性,引进Small-world网络拓扑结构,参照此结构,建立图书馆信息资源存储中心与来源渠道之间的直接访问接口,构建图书馆信息资源分布结构模型;使用关联规则挖掘技术中的Apriori算法,提取图书馆信息资源特征;建立针对特征的空间映射函数,通过对特征的辨识,实现信息资源的聚类融合。以某地区大型公共图书馆为例,文章通过设计对比实验的方式,证明设计的方法在实际应用中的整合效果较好,可以提高整合后图书馆内信息资源的集成度与查全率。In order to improve the recall rate of information resources in the local public library database,a new integration method for library information resources was designed by introducing association rule mining technology.In order to ensure that the constructed model and resource distribution have strong adaptability,the Small-world network topology structure is introduced.Referring to this structure,a direct access interface between the library information resource storage center and the source channel is established,and the library information resources distribution structure model is constructed.The Apriori algorithm of association rule mining technology is used to extract library information resource features.The spatial mapping function for features is established,and the clustering fusion of information resources is realized through the feature identification.Taking a large public library in a certain area as an example,by designing a comparative experiment,it is proved that the designed method has a better integration effect in practical application,and can improve the integration and recall rate of information resources in the library after integration.
关 键 词:关联规则 整合方法 信息资源 特征提取 聚类融合
分 类 号:TN911[电子电信—通信与信息系统]
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