Tendency of Restaurant Reviews Mining Model Combining FP-Tree Algorithm

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/).

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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  -