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Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

机译:应用智能技术的数字图书馆中的知识检索

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Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user's interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings.
机译:如今,数量巨大的异构和分布式信息存储在数字大学中。探索在线集合来查找与用户兴趣相关的知识是一项具有挑战性的工作。人工智能和语义网络提供了一个常见的框架,允许以有效的方式共享和重复使用的知识。在这项工作中,我们提出了一种基于对这些对象中录制的语义元数据的分析和专家系统技术的应用,提出了一种在大型数字收藏中发现电子学习对象的综合方法。我们使用基于案例的推理方法来开发来自在线存储库的有效检索知识的原型。我们建议一个语义搜索引擎的概念架构。 Ontous是一种协作努力,提出了用户和数字图书馆之间一种新的互动形式,后者适应用户及其周围环境。

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