The study of the removal redundant association rules based on Hypergraph in Large data environment

DOI

10.2991/icmemtc-16.2016.115How to use a DOI?

Keywords

Large data; hypergraph; redundant association rules

Abstract

This paper takes the high dimensional data for large data mining technology as the research object, using the adjacency matrix and directed hypergraph detection relationship between association rule items, explores the method, classification based on spanning tree removal algorithm for detection of large data condition redundant association rules, the algorithm can effectively improve the efficiency of association rule mining, the need to reduce the actual processing time.

Copyright

© 2016, 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  - Xin-liang Li
AU  - Li-yun Liu
PY  - 2016/04
DA  - 2016/04
TI  - The study of the removal redundant association rules based on Hypergraph in Large data environment
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 587
EP  - 591
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.115
DO  - 10.2991/icmemtc-16.2016.115
ID  - Li2016/04
ER  -