A two-level Product Recommender for E-commerce Sites by Using Sequential Pattern Analysis

Authors

  • Shahram Jamali University of Mohaghegh Ardabili, Ardabil, IRAN
  • Yahya Dorostkar Navaei University of Mohaghegh Ardabili, Ardabil, IRAN

Keywords:

Product recommendation system, two-level RPS, e-commerce, clustering, sequential pattern analysis

Abstract

With the development of communication networks and rapid growth of their applications, huge amount of information have been produced. Major part of these information are in electronic stores, and hence it's really hard to find desired products inside huggermugger. Product Recommendation System (PRS) tries to solve this problem by giving appropriate and fast recommendations to the customers. This paper proposes a two-level product recommender for E-commerce sites. At first, the available products are clustered by using C-Means algorithm to create groups of products with similar characteristics. Then, the second level considers the customers’ behavior and their purchase history for drawing the relationships between products by using Sequential Pattern Analysis (SPA) method. These relationships, eventually, will lead to appropriate recommendation for customers and also increases the likelihood of selling related products in electronic transactions. Extensive numerical simulations over UCI transactions 10k dataset indicates that 87% of records in mined sequential patterns are predicted correctly and the accuracy of recommendations is more than other RPSs.

Downloads

Download data is not yet available.

Author Biographies

  • Shahram Jamali, University of Mohaghegh Ardabili, Ardabil, IRAN
    Department of Computer Engineering
  • Yahya Dorostkar Navaei, University of Mohaghegh Ardabili, Ardabil, IRAN
    Department of Computer Engineering

Downloads

Published

01-04-2016

Issue

Section

Issue on Electrical and Electronic Engineering

How to Cite

Jamali, S., & Navaei, Y. D. (2016). A two-level Product Recommender for E-commerce Sites by Using Sequential Pattern Analysis. International Journal of Integrated Engineering, 8(1). https://penerbit.uthm.edu.my/ojs/index.php/ijie/article/view/1330