Study on the Application of the Theory of Rough Sets to Text Excavation

DOI

10.2991/icieac-14.2014.26How to use a DOI?

Keywords

rough set; data excavation; text excavation; attribute reduction; correlation rules

Abstract

The rough set theory is a new calculation which deduces the concept categorization rules through attribute reduction with the categorization capacity remaining unchanged, and has wide application to data excavation and text excavation. This paper focuses on the analysis and improvement of the application of the rough set theory to text excavation, embracing the two aspects of attribute reduction based on clear matrix and correlation rules based on the Apriori algorithm. Compared with the classic algorithms, the improved algorithm can cut down a great deal on the expenditure of time and space in its operation, and improves considerably in its performance of processing the large-scale text database excavation. This research result has great theoretical significance to the application of the rough set theory and its algorithm to text excavation.

Copyright

© 2014, 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  - Dali Yin
AU  - Yan Yan
PY  - 2014/03
DA  - 2014/03
TI  - Study on the Application of the Theory of Rough Sets to Text Excavation
BT  - Proceedings of the 2nd International Conference on Information, Electronics and Computer
PB  - Atlantis Press
SP  - 117
EP  - 120
SN  - 1951-6851
UR  - https://doi.org/10.2991/icieac-14.2014.26
DO  - 10.2991/icieac-14.2014.26
ID  - Yin2014/03
ER  -