Open AccessCluster analysis of Xi’an restaurants by Self-organizing maps
Author(s) -
Jie Kong,
Meng Ren
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/2/022121
Subject(s) - self organizing map , cluster analysis , social network analysis , segmentation , computer science , visualization , cluster (spacecraft) , china , data science , data mining , artificial intelligence , geography , social media , world wide web , archaeology , programming language
To investigate the segmentation features of restaurants in Xi’an, China, the Self-organizing maps are applied in this study to analyse the information of online reviews obtained from Dazhong Dianping, which is a famous Chinese social network. Through the clustering and visualization performed by Self-organizing maps, 10 segments of restaurants are identified and some representative features are summarized. The findings of this study could help managers to improve restaurant competitiveness, as well as customers’ decision making.