Optimization of Research on Case-base Structure based on Information Entropy
Bin Huang, Hao Li
Available Online June 2017.
- https://doi.org/10.2991/msmi-17.2017.16How to use a DOI?
- case-base management; the redundancy control; entropy; weights
- The core step of Case-based Reasoning is to retrieval and match the case with the fault feature accurately and efficiently, the scale of the case library is becoming larger because of the case studies feature, but the redundancy is becoming clearer at the same time, it influences the accuracy. The effective way to control the redundancy is to define the attributes which can distinguish the cases, the paper determines the weight of the case characteristics with the theory of entropy, making it more reasonable to divide the characteristics and more effective to organize the case, in order to control the redundancy of the case-base, thus improves the effectiveness of Case-Based Reasoning.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Bin Huang AU - Hao Li PY - 2017/06 DA - 2017/06 TI - Optimization of Research on Case-base Structure based on Information Entropy BT - Proceedings of the 2017 International Conference on Management Science and Management Innovation (MSMI 2017) PB - Atlantis Press SP - 67 EP - 71 SN - 2352-5428 UR - https://doi.org/10.2991/msmi-17.2017.16 DO - https://doi.org/10.2991/msmi-17.2017.16 ID - Huang2017/06 ER -