Construction of Multidimensional Data Knowledge Base by Improved Classification Association Rule Mining Algorithm

DOI

10.2991/emcm-16.2017.171How to use a DOI?

Keywords

Multidimensional data; Knowledge base; Association rule; Classification; FP-Growth

Abstract

Firstly, this paper analyzes the advantages and disadvantages of the existing association rules mining algorithm, and gives the method of multidimensional data analysis. In order to remedy the defects, this paper discusses and improves clustering and classification algorithm for constructing intelligent knowledge base. The paper presents construction of multidimensional data knowledge base by improved classification association rule mining algorithm. The effectiveness of the proposed method is analyzed by an example.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Qing Tan
PY  - 2017/02
DA  - 2017/02
TI  - Construction of Multidimensional Data Knowledge Base by Improved Classification Association Rule Mining Algorithm
BT  - Proceedings of the 2016 7th International Conference on Education, Management, Computer and Medicine (EMCM 2016)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/emcm-16.2017.171
DO  - 10.2991/emcm-16.2017.171
ID  - Tan2017/02
ER  -