Tendency of Restaurant Reviews Mining Model Combining FP-Tree Algorithm
Authors
Qixiang Wang, Chen Li, Guanyang He, Xinyi Xu, Jing Li
Corresponding Author
Qixiang Wang
Available Online April 2015.
- DOI
- 10.2991/ameii-15.2015.57How to use a DOI?
- Keywords
- FP-Tree; Restaurant comment; Emotion tendency; UGC; POS template
- Abstract
A restaurant review tendentious mining method that combines FP-Tree algorithm is presented to dig and identify high-frequency noun pairs in reviews associated with services, the environment, food, to name just a few, by mining association rules. A feature word dictionary is established and Training the training set for sentence template which is form of Part of Speech tags and match the comments with different sentence template to calculate with feature score and total score. This idea can also be used to analyze product features and areas in which UGC score calculation is needed.
- 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/).
Cite this article
TY - CONF AU - Qixiang Wang AU - Chen Li AU - Guanyang He AU - Xinyi Xu AU - Jing Li PY - 2015/04 DA - 2015/04 TI - Tendency of Restaurant Reviews Mining Model Combining FP-Tree Algorithm BT - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics PB - Atlantis Press SP - 313 EP - 319 SN - 2352-5401 UR - https://doi.org/10.2991/ameii-15.2015.57 DO - 10.2991/ameii-15.2015.57 ID - Wang2015/04 ER -