在整个系统设计开发中电子商务网站案例的知识表示、相应推理搜索算法的设计是首先要解决的问题。
The essential problems of IDSEB designing and development are knowledge representation of EC website cases and designing of the corresponding reasoning algorithms.
与传统的基于规则的系统相比，基于案例推理的系统具有简化知识获取、便于知识积累等优点。
Comparing to traditional rule-based system, it has many advantages, which can predigest knowledge gathering and accumulate knowledge easily.
从基于案例推理技术的理论出发，采用物元的知识表示方法，定义了物元可拓与或网。
This paper, using the casebased reasoning techniques, adopts a methodology of extension information representation. And matter element extension information AND/OR nets is defined.
从基于案例推理机制入手，阐述了基于案例推理知识库系统的工作过程和原理，提出了系统设计的方法。
With the mechanism of the technology based on case-based reasoning, the working course and principle are expatiated, and then a system-designed method is proposed.
通过此模型使用基于动态数据流挖掘的案例推理技术，对数据进行实时挖掘，产生连续、动态的临时案例库，实现知识库的实时更新，从而满足实际问题变化的需要。
Through this model the system can mine real-time datum, produce continuous, dynamic temporary cases, update the knowledge base in real time and meet the needs of the practical problems.
基于规则的推理（RBR）和基于案例的推理（CBR）则是知识工程中两类实用有效的推理方式。
Rule-based and case-based reasoning are two important efficient reasoning methods in artificial intelligence field.
提出了基于知识的毛纺产品工艺设计智能模型，通过基于案例（C BR）和基于规则的推理（RBR）以及人工神经网络（ANN）等关键技术的引入，提高了系统解决实际问题的能力。
This paper presents the wool textile process intelligent design model(WTPIDM), by the introduction of CBR, RBR, ANN technologies, improving the system capability to solve the problems.
提出了基于知识的毛纺产品工艺设计智能模型，通过基于案例（C BR）和基于规则的推理（RBR）以及人工神经网络（ANN）等关键技术的引入，提高了系统解决实际问题的能力。
This paper presents the wool textile process intelligent design model(WTPIDM), by the introduction of CBR, RBR, ANN technologies, improving the system capability to solve the problems.
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