Fuzzy Set Based Web Opinion Text Clustering Algorithm
Hongxin Wan, Yun Peng
Available Online December 2015.
- 10.2991/icmmcce-15.2015.501How to use a DOI?
- Opinion text, Clustering analysis, Fuzzy set, Membership function
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.
- © 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/).
Cite this article
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 -