Collaborative Filtering for Bargaining and Customer Feedback in E-Commerce-Reference-Cited by-同舟云学术

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Collaborative Filtering for Bargaining and Customer Feedback in E-Commerce

Published:2023-05-17 Issue: Volume: Page:
ISSN:
Container-title:2023 7th International Conference on Intelligent Computing and Control Systems (ICICCS)
language:
Short-container-title:

Author:

Jebamalar Belshia¹,Sudha K.²,Maheswari B.²,Nalini M.³,Dinesh M.G.⁴,Siva Subramanian R⁵

Affiliation:

1. S.A Engineering College,Dept of CSE

2. R.M.D Engineering College,Dept of CSBS

3. Associate Professor, Department of CSE, S.A. Engineering College

4. Easa College of Engg and Tech,Dept of CSE

5. RMK College of Engg and Tech,Dept of CSE

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10142228/10142218/10142348.pdf?arnumber=10142348

Reference15 articles.

1. Iterative Collaborative Filtering for Sparse Noisy Tensor Estimation

2. Multi-graph Convolution Collaborative Filtering

3. A survey on customer relationship management

4. Technology-enabled online aggregated market for smallholder farmers to obtain enhanced farm-gate prices

5. Ensemble variable selection for Naïve Bayes to improve Customer Behaviour Analysis;prabha;Computer Systems Science & Engineering,2022

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advances in Data Processing, Machine Learning, and Data Security;Advances in Electronic Commerce;2024-09-27

2. Advancing E-Commerce Security;Advances in Electronic Commerce;2024-09-27

3. HMGR: A Hybrid Model for Geolocation Recommendation;Big Data – BigData 2023;2023

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