Research and Implementation of RDF Knowledge Reasoning based on Concept Semantic Network Graph;
提出了一种符合图形界面下建立通用电网模型的知识推理方法。
Machine learning and data mining techniques are applied to acquire knowledge and build a concept reasoning network based on semantic dictionary and large training set.
在已有的英语语义词典及大量训练集的基础上，应用机器学习、数据挖掘等技术进行知识获取并最终形成若干个概念推理网。
It is shown that the semantic network of concept can improve the result of the question search of NL-WAS system effectively.
实验结果表明，本算法获得的概念语义网络可以有效地提高问题检索的效果。
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