E-COMMERCE RECOMMENDATION SYSTEM BASED ON DEMAND CLUES

Author Name: 1. Ibnath Naour Reeve, 2. Taushiqul Alam, 3. Marzia Rahman Munia, 4. Ahnaf Atif Showmik, 5. Muhammad Fahim Faisal

Volume/Issue: 04/11

Country: China, Bangladesh

DOI NO.: 08.2020-25662434 DOI Link: https://doi-ds.org/doilink/05.2024-41995257/UIJIR

Affiliation:

1. Bachelor’s Student, Department of Computer Science and Communication Engineering, University of Science and Technology Beijing, Beijing, China. ibnath420@hotmail.com
2. Master’s Student, Department of Economics and International Trade, University of Science and Technology Beijing, Beijing, China. taushiqulalam@icloud.com
3. Bachelor’s Student, Department of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China. mmarziarahman@gmail.com
4. Bachelor’s Student, Department: Bachelor of Business Administration (BBA), Bangladesh University of Professionals, Dhaka, Bangladesh. ahnafatifshowmik@gmail.com
5. Bachelor’s Student, Department of Electrical and Electronic Engineering, BRAC University, Dhaka, Bangladesh. fad@gmail.com

ABSTRACT

Traditional e-commerce recommendation systems use offline methods to analyze and process customer demand information, thus losing timeliness. In order to solve related problems, a demand-based recommendation system came up for leads. The basic model, data structure, key algorithms and operation process of the system are given. The system uses demand clue tracking to collect the current needs of customers, seek information to conduct demand tendency analysis; and match and retrieve products and customers that need to be recommended in the demand VS product overlay space. Online marketing simulation experiments show that the system have good timely response ability and high customer satisfaction.

Key words: E-commerce, Recommendation system, On-line demand clues