Opinion Text Features Finding and Evaluation Algorithm Based on Rough Set

DOI

10.2991/icmmcce-15.2015.502How to use a DOI?

Keywords

rough set, features finding, opinion text, key words

Abstract

Follow the development of Internet, more and more opinion texts are written on social media web by people, and it is very difficult to find the features in these texts because of the texts scale. We propose an algorithm to find features from key words by words reduction method, which considers the correlation between words, and candidate words can be divided into key words and secondary words. Using rough set to discriminate candidate words we can get the key words out of the candidate words, thus get the features of opinion texts. After features finding we can carry out the evaluation based on fuzzy set. Rough set can reduce the data size and algorithm complexity and improve the accuracy of the algorithm. The algorithm of finding features and features evaluation in opinion texts is described in detail by example in this paper.

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  - Hongxin Wan
AU  - Yun Peng
PY  - 2015/12
DA  - 2015/12
TI  - Opinion Text Features Finding and Evaluation Algorithm Based on Rough Set
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.502
DO  - 10.2991/icmmcce-15.2015.502
ID  - Wan2015/12
ER  -