Design and Implementation of Retrieval System of Network Learning Resources Based on Semantic Web

نویسندگان

  • Haibin Hu
  • Shipin Chen
چکیده

The gradual finding of large quantities of low-relevant or even non-relevant information is returned by the traditional keyword-based query. To further improve the efficiency and quality of network learning resources retrieval, this article designs a generic Semantic Web-based e-learning resources retrieval system model and achieves B/S mode of semantic retrieval prototype system, considering the influence of various factors for the similarity and correlation, such as degree of semantic overlap, semantic distance, semantic hierarchy, and property relation. By comparing with the traditional query, the retrieval results showed that the semantic retrieval methods to ensure precision in the case of a higher recall rate.

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تاریخ انتشار 2015