Research on User Profile of Characteristic Towns with Cultural Tourism Based on K-means Clustering

被引：0
|
作者：
Wang, Yali [1 ]
Feng, Lu [1 ]
机构：
[1] Shandong Youth Univ Polit Sci, Sch Econ & Management, Jinan 250000, Shandong, Peoples R China
来源：
PROCEEDINGS OF 2021 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND INFORMATION SYSTEMS (ICAIIS '21) | 2021年
关键词：
User profile; K-means clustering; Culture;
D O I：
10.1145/3469213.3472777
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
User profile is more and more used in scenic spot marketing. Through a survey of 350 consumers in the holy land of Qufu Nishan, this paper adopts the K-means clustering method and finally divides the consumers into five categories, namely research and exchange users, negative inheritance user, cultural-deficient user, carry forward class of users, ignore culture users. By comparing and analyzing the differences of these five types of consumers, this paper hopes to provide some references for the marketing of this characteristic town.
引用
收藏
页数：4
相关论文
共 50 条
  • [41] Analysis and Research on Enterprise Resumption of Work and Production Based on K-means Clustering
    Wang Peiyi
    Ma Longfei
    Li Xianglong
    Zhang Lu
    Qin Hao
    Yao Bin
    Ding Yifeng
    2021 IEEE 6TH INTERNATIONAL CONFERENCE ON BIG DATA ANALYTICS (ICBDA 2021), 2021, : 169 - 174
  • [42] Research of Power User Load Classification Method Based on K-means and FSVM
    Sun RongQi
    Xiao XueQuan
    Zhou Feng
    Zhou YuShan
    PROCEEDINGS OF 2019 IEEE 3RD INFORMATION TECHNOLOGY, NETWORKING, ELECTRONIC AND AUTOMATION CONTROL CONFERENCE (ITNEC 2019), 2019, : 2138 - 2142
  • [43] Application of an improved k-means clustering algorithm in power user grouping
    Wu Gang
    Zhang Dongdong
    Fan Shengrong
    INTERNATIONAL JOURNAL OF NUMERICAL MODELLING-ELECTRONIC NETWORKS DEVICES AND FIELDS, 2022, 35 (04)
  • [44] Research of buffer overflow vulnerabilities detection based on novel K-means clustering
    Cao, Laicheng
    Su, Xiangqian
    Wu, Youxiao
    Journal of Computational Information Systems, 2015, 11 (04): : 1453 - 1461
  • [45] Research on Clustering Routing Algorithm based on K-means plus plus for WSN
    Yang, Xiang
    Yan, Yu
    Deng, Dengteng
    PROCEEDINGS OF 2017 6TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT 2017), 2017, : 330 - 333
  • [46] Research on customer clustering for energy network marketing system based on K-means
    Xinwu, Li
    Energy Education Science and Technology Part A: Energy Science and Research, 2013, 31 (02): : 1099 - 1104
  • [47] Web User Session Clustering Using Modified K-Means Algorithm
    Poornalatha, G.
    Raghavendra, Prakash S.
    ADVANCES IN COMPUTING AND COMMUNICATIONS, PT 2, 2011, 191 : 243 - +
  • [48] Selection of K in K-means clustering
    Pham, DT
    Dimov, SS
    Nguyen, CD
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE, 2005, 219 (01) : 103 - 119
  • [49] Research of Electrical Equipment State Identification Based on K-means Clustering Algorithm
    Lei, Liting
    Xu, Hui
    Fan, Rongrong
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND ELECTRONIC TECHNOLOGY, 2016, 48 : 196 - 200
  • [50] Ideological and Political Education Management Research based on Improved K-means Clustering
    Jing, Liu
    2016 INTERNATIONAL CONFERENCE ON ROBOTS & INTELLIGENT SYSTEM (ICRIS), 2016, : 213 - 216
12345