Proceedings of the 2016 International Conference on Engineering Science and Management

Simple Mining Method of Rich Text Data from User Feedback and Its Application

Authors
Huali Cai, Fang Wu, Qi Duan, Jian Kang, Yawei Jiang
Corresponding Author
Huali Cai
Available Online August 2016.
DOI
10.2991/esm-16.2016.54How to use a DOI?
Keywords
Rich text, data mining, complaint rate introduction
Abstract

At present, many large-scale consumer goods or food suppliers would receive a lot of feedback data from consumers, which is vital to the improvement of corporate management. Nevertheless, these data fail to be fully utilized or labeled manually piece by piece due to employees' poor skills or officers' lack of awareness in most of these enterprises. This paper investigates a simple method of handling such data. First, several basic databases are built, including index system, industry topic lexicon and emotion lexicon. Then, the polarity judgment method is studied. Finally, criticism rate, appreciation rate and suggestion rate are studied and determined. All these rates have gained application in a large-scale enterprise of China and received good effect.

Copyright
© 2016, 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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Volume Title
Proceedings of the 2016 International Conference on Engineering Science and Management
Series
Advances in Engineering Research
Publication Date
August 2016
ISBN
10.2991/esm-16.2016.54
ISSN
2352-5401
DOI
10.2991/esm-16.2016.54How to use a DOI?
Copyright
© 2016, 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  - Huali Cai
AU  - Fang Wu
AU  - Qi Duan
AU  - Jian Kang
AU  - Yawei Jiang
PY  - 2016/08
DA  - 2016/08
TI  - Simple Mining Method of Rich Text Data from User Feedback and Its Application
BT  - Proceedings of the 2016 International Conference on Engineering Science and Management
PB  - Atlantis Press
SP  - 234
EP  - 235
SN  - 2352-5401
UR  - https://doi.org/10.2991/esm-16.2016.54
DO  - 10.2991/esm-16.2016.54
ID  - Cai2016/08
ER  -