Collaborative case-based reasoning for knowledge discovery of elders health assessment system.
Collaborative case-based reasoning for knowledge discovery of elders health assessment system.
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DOI：
10.2174/1874120701408010068
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Zhu Y
中科院分区：
文献类型：
--
作者：
Hu P;Gu DX;Zhu Y
现有基于单例库推理的老年人健康评估（EHA）系统智能水平低、协调性差、评估决策支持能力有限。为了有效支持EHA系统的知识重用，本文提出协同案例推理，并将其应用到EHA系统的整个知识重用过程中。提出EHA知识复用系统多案例库推理应用框架，研究案例表示、案例检索算法、案例优化与修正、复用等关键技术。在案例表示方面，采用基于XML的多案例表示进行案例组织和存储，方便案例检索和管理。在检索方法方面，提出了最近邻知识引导方法。鉴于EHA的复杂性，采用加权欧氏距离的灰色关联分析来衡量相似度，以提高案例检索的准确性。
The existing Elders Health Assessment (EHA) system based on single-case-library reasoning has low intelligence level, poor coordination, and limited capabilities of assessment decision support. To effectively support knowledge reuse of EHA system, this paper proposes collaborative case reasoning and applies it to the whole knowledge reuse process of EHA system. It proposes a multi-case library reasoning application framework of EHA knowledge reuse system, and studies key techniques such as case representation, case retrieval algorithm, case optimization and correction, and reuse etc.. In the aspect of case representation, XML-based multi-case representation for case organization and storage is applied to facilitate case retrieval and management. In the aspect of retrieval method, Knowledge-Guided Approach with Nearest-Neighbor is proposed. Given the complexity of EHA, Gray Relational Analysis with weighted Euclidean Distance is used to measure the similarity so as to improve case retrieval accuracy.