Emergencies prediction model based on efficient mining for micro-blog

DOI

10.2991/iccset-14.2015.53How to use a DOI?

Keywords

association rules; emergencies; gene expression programming

Abstract

In the case of the increasing amount of micro-blog information data, traditional mining techniques used to forecast emergency have tedious defects, like time-consuming and poor stability and so on. To solve these problems, an emergencies predictive method of efficient algorithm for micro-blog content mining is proposed, combining niche technology and gene expression programming in the data mining technology, through penalty function to set support threshold, and search for stronger association rules during data mining, which benefits effectively avoiding premature algorithm, so as to solve the problem of redundant rules, realize emergencies prediction . Experiment simulation proved emergencies prediction method for efficient mining based on efficient micro-blog content has high accuracy and strong robustness.

Copyright

© 2015, 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  - Wenxia Bi
PY  - 2015/01
DA  - 2015/01
TI  - Emergencies prediction model based on efficient mining for micro-blog
BT  - Proceedings of the 2014 International Conference on Computer Science and Electronic Technology
PB  - Atlantis Press
SP  - 248
EP  - 252
SN  - 2352-538X
UR  - https://doi.org/10.2991/iccset-14.2015.53
DO  - 10.2991/iccset-14.2015.53
ID  - Bi2015/01
ER  -