基于元数据语义模型的数字资源Top-N检索

Top-N Retrieval of Digital Resource Based on Metadata Semantics Model

提出一种以元数据为语义基础的用户查询模型用于数字资源的检索。通过改进传统关系库中的Top-N算法,以不同数据类型和元数据为语义基础,给出一种基于语义的相似度度量新方法。在此基础上开发一套智能检索系统,并将其用于上海教育资源库。应用结果表明,该系统可有效提高信息检索的准确度。

This paper presents a query model based on semantic meta-model to search digital resources. By improving Top-N algorithm in traditional relational database, a novel similarity evaluation method is proposed based on the different kinds of data type and the semantic meta-model. Based on the method, an intelligent querying system is developed, which is used in Shanghai Educational Resources Center. Actual application shows that it can improve the query precision effectively.