A Review on Consumer Behavior Prediction using Data Mining Techniques

被引：0
|
作者：
Kareena [1 ]
Kapoor, Nitika [1 ]
机构：
[1] Chandigarh Univ, Univ Inst Engn CSE, Mohali, Punjab, India
来源：
PROCEEDINGS OF THE 2019 6TH INTERNATIONAL CONFERENCE ON COMPUTING FOR SUSTAINABLE GLOBAL DEVELOPMENT (INDIACOM) | 2019年
关键词：
Data mining; Consumer behavior; technique; analysis;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Consumer behavior plays an important role in today's world because it is not only concerned with business world but it has lot to do with every field like healthcare, banking, manufacturing, education etc. And to predict the consumer behavior, data mining techniques plays an important role, so a review has been done to analyze the best technique among various techniques like Decision Tress, SVM, Random Forest, Genetic Algorithm etc and the type of data which is used for prediction is either the past purchase history or the reviews given by customers in almost every paper and SVM comes out to be the best technique among various techniques.
引用
收藏
页码：1089 / 1093
页数：5
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