摘要：

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。

关键词: 元数据, 语义, Top-N算法, 信息检索

Abstract:

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.

Key words: metadata, semantics, Top-N algorithm, information retrieval

中图分类号: 

• TP391