Towards an agent approach in a federating search of learning objects

Edgar Alan Cavillo-Moreno, J. M. Arteaga, C. A. O. Zezzatti, R. Salgado, F. A. Rodríguez
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Abstract

A traditional search applied in a federation of learning objects repositories consumes a lot of resources in time, large numbers of queries and registers. The main improvement proposed in this work is the insertion of intelligent agents in order to have pertinent results with less consuming resources and covering the expectations of user communities. Additional advantages using agent approach in a federated search is possible to get the information in a semantic way the searches of learning objects.
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学习对象联合搜索中的代理方法研究
在学习对象存储库联合中应用传统的搜索会消耗大量的时间资源、大量的查询和注册。在这项工作中提出的主要改进是智能代理的插入,以便以更少的资源消耗和覆盖用户群体的期望获得相关的结果。在联邦搜索中使用代理方法的其他优点是可以通过学习对象的搜索以语义的方式获取信息。
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