Identification of Consumer Buying Patterns using KNN in E-Commerce Applications

Title

Identification of Consumer Buying Patterns using KNN in E-Commerce Applications

Creator

Yasin W.; Harimoorthy K.; Vetriveeran D.

Description

In recent days, with the advancement of technologies, people use electronic medium to carry out their businesses. E-commerce is a process of allowing people to buy and sell products online using electronic medium. E-commerce has a wide range of customer base as well. The data generated through transaction helps the enterprises to develop the marketing strategy. The growth of this e-commerce application depends on several factors. Some of the factors are follows 1) Customer demand, 2) Analyzing buying pattern of the users, 3) Customer retention, 4) dynamic pricing etc. It is very difficult to analyze the buying pattern of customers as there is a wide range of customer base in the online platform. To overcome this problem, this research study discusses about the challenges and issues in e-commerce applications, also identifies and analyses the buying patterns of customer using various machine learning techniques. From the implementation it is identified that, KNN algorithm performed well while comparing it with various other machine learning algorithms. Performances of these algorithms have been analyzed using various matrices. For analyzing, the model is tested using e-commerce dataset (Amazon dataset downloaded from Kaggle.com). From the analysis it found that KNN algorithm computes and predicts better compared to other machine learning algorithms either Nae Bayes, or Random Forest, or Logistic Regression etc. 2023 IEEE.

Source

Proceedings - 2023 3rd International Conference on Pervasive Computing and Social Networking, ICPCSN 2023, pp. 187-192.

Date

2023-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

buying behavior; Consumer behavior analysis; E- Commerce applications; K-Nearest Neighbor; Machine Learning

Coverage

Yasin W., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Karnataka, Bangalore, India; Harimoorthy K., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Karnataka, Bangalore, India; Vetriveeran D., CHRIST(Deemed to Be University), Department of Computer Science and Engineering, Karnataka, Bangalore, India

Rights

Restricted Access

Relation

ISBN: 979-835032284-2

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICPCSN58827.2023.00036

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