Proceedings of the 2017 International Conference on Management Science and Management Innovation (MSMI 2017)

Optimization of Research on Case-base Structure based on Information Entropy

Authors
Bin Huang, Hao Li
Corresponding Author
Bin Huang
Available Online June 2017.
DOI
https://doi.org/10.2991/msmi-17.2017.16How to use a DOI?
Keywords
case-base management; the redundancy control; entropy; weights
Abstract
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.

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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  -