Fuzzy Set Based Web Opinion Text Clustering Algorithm

DOI

10.2991/icmmcce-15.2015.501How to use a DOI?

Keywords

Opinion text, Clustering analysis, Fuzzy set, Membership function

Abstract

With the development of social media, people like to express their views on the Web. Because people express their views casually, which makes the opinion text contain a lot of uncertain and unstructured contents, and it is difficult to cluster the text by normal classification methods. An algorithm of opinion text clustering based on fuzzy set is proposed, which adopts the key words as classifying attributes and calculate the membership degree by fuzzy function, thus can deal with the uncertain and unstructured contents well. Also the algorithm proposed can improve the time and space efficiency, and increase the robustness compared with other classification algorithms.

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  - Fuzzy Set Based Web Opinion Text Clustering Algorithm
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-15.2015.501
DO  - 10.2991/icmmcce-15.2015.501
ID  - Wan2015/12
ER  -