语义网络作为一种模拟人类的语言的知识表示方法，在开发智能系统和机器学习领域中具有重要的地位和作用。
As the knowledge representation methods simulating human language, semantic network has significant impact and position in intelligence system development and machine learning fields.
第二章详细介绍了基于本体论的语义网络模型理论，包括语义网络模型的结构、知识表示及推理机制。
Thesecond chapter introduced semantic network model theory in detail based on ontology, including model structure, knowledge expression and inferential mechanism.
语义网络作为表示知识的主要方法，成为知识库组成的主要形式，从而引出知识库的维护及推理的实现。
The semantic network is the main method of representing knowledge, and is becoming principal form of component of knowledge base, so educes maintaining knowledge base and implementing inference.
本文提出了一个属性文法计算模型与语义网络表示模型相结合的综合知识表示模型。
This paper presents a synthetical knowledge representation model integrating attribute grammar evaluation model with semantic network representation model.
针对旋转机械故障诊断专家系统中的知识表示问题，讨论了语义网络的知识表示方法。
Aiming at knowledge representation problem of expert system for rotary machinery fault diagnosis, semantic net knowledge representation is discussed.
但是在现在的研究中，大部分工作都集中讨论如何解决用语义网络表示某种具体问题，对语义网络中知识的获取和约简缺乏关注，思考不深。
However, most present research work pay more attention on the express the knowledge in some fields by semantic network, rather than the other aspects of semantic network.
文本推理在自然语言处理的应用中占有极为重要的位置，本文介绍了基于知网的一种推理方法，该方法以语义网络的形式表示知网中的知识，利用“标记传递”实现推理。
Text inference is central to natural language applications. This paper presents an inference method based on HowNet, which organizes knowledge with semantic net and infers with marker passing.
这三种知识表示方法为：逻辑表示法、语义网络和产生式系统。
The three methods are: logic representation, semantic network, rule-based system.
这三种知识表示方法为：逻辑表示法、语义网络和产生式系统。
The three methods are: logic representation, semantic network, rule-based system.
应用推荐