Real-Time Prediction of Online Shoppers' Purchasing Intention Using Random Forest

被引：7
|
作者：
Baati, Karim [1 ]
Mohsil, Mouad [2 ]
机构：
[1] Teolia Consulting, 12-14 Rond Point Champs Elysees, F-75008 Paris, France
[2] Teolia DA, 12-14 Rond Point Champs Elysees, F-75008 Paris, France
来源：
ARTIFICIAL INTELLIGENCE APPLICATIONS AND INNOVATIONS, AIAI 2020, PT I | 2020年 / 583卷
关键词：
Real-time online shopper behavior; Marketing offers in online stores; Random forest; POSSIBILISTIC CLASSIFIER;
D O I：
10.1007/978-3-030-49161-1_4
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we suggest a real-time online shopper behavior prediction system which predicts the visitor's shopping intent as soon as the website is visited. To do that, we rely on session and visitor information and we investigate naive Bayes classifier, C4.5 decision tree and random forest. Furthermore, we use oversampling to improve the performance and the scalability of each classifier. The results show that random forest produces significantly higher accuracy and F1 Score than the compared techniques.
引用
收藏
页码：43 / 51
页数：9
相关论文
共 50 条
  • [1] Real-time prediction of online shoppers' purchasing intention using multilayer perceptron and LSTM recurrent neural networks
    Sakar, C. Okan
    Polat, S. Olcay
    Katircioglu, Mete
    Kastro, Yomi
    NEURAL COMPUTING & APPLICATIONS, 2019, 31 (10): : 6893 - 6908
  • [2] Real-time prediction of online shoppers’ purchasing intention using multilayer perceptron and LSTM recurrent neural networks
    C. Okan Sakar
    S. Olcay Polat
    Mete Katircioglu
    Yomi Kastro
    Neural Computing and Applications, 2019, 31 : 6893 - 6908
  • [3] Real-time WiFi localization of heterogeneous robot teams using an online random forest
    Balaguer Benjamin
    Gorkem Erinc
    Stefano Carpin
    Autonomous Robots, 2015, 39 : 155 - 167
  • [4] Real-time WiFi localization of heterogeneous robot teams using an online random forest
    Benjamin, Balaguer
    Erinc, Gorkem
    Carpin, Stefano
    AUTONOMOUS ROBOTS, 2015, 39 (02) : 155 - 167
  • [5] Real-time prediction of tunnel face conditions using XGBoost Random Forest algorithm
    Lei-jie Wu
    Xu Li
    Ji-dong Yuan
    Shuang-jing Wang
    Frontiers of Structural and Civil Engineering, 2023, 17 : 1777 - 1795
  • [6] Real-time prediction of tunnel face conditions using XGBoost Random Forest algorithm
    Leijie WU
    Xu LI
    Jidong YUAN
    Shuangjing WANG
    Frontiers of Structural and Civil Engineering, 2023, 17 (12) : 1777 - 1795
  • [7] Real-time prediction of tunnel face conditions using XGBoost Random Forest algorithm
    Wu, Lei-jie
    Li, Xu
    Yuan, Ji-dong
    Wang, Shuang-jing
    FRONTIERS OF STRUCTURAL AND CIVIL ENGINEERING, 2023, 17 (12) : 1777 - 1795
  • [8] Real-time prediction of high-density EAST disruptions using random forest
    Hu, W. H.
    Rea, C.
    Yuan, Q. P.
    Erickson, K. G.
    Chen, D. L.
    Shen, B.
    Huang, Y.
    Xiao, J. Y.
    Chen, J. J.
    Duan, Y. M.
    Zhang, Y.
    Zhuang, H. D.
    Xu, J. C.
    Montes, K. J.
    Granetz, R. S.
    Zeng, L.
    Qian, J. P.
    Xiao, B. J.
    Li, J. G.
    NUCLEAR FUSION, 2021, 61 (06)
  • [9] A gradient boosting classifier for purchase intention prediction of online shoppers
    Abdullah-All-Tanvir
    Khandokar, Iftakhar Ali
    Islam, A. K. M. Muzahidul
    Islam, Salekul
    Shatabda, Swakkhar
    HELIYON, 2023, 9 (04)
  • [10] Real-time Quality Prediction of Casting Billet Based on Random Forest Algorithm
    Ye, Xueming
    Wu, Xing
    Guo, Yike
    PROCEEDINGS OF THE 2018 IEEE INTERNATIONAL CONFERENCE ON PROGRESS IN INFORMATICS AND COMPUTING (PIC), 2018, : 140 - 143
12345