OntoCommerce: Incorporating Ontology and Sequential Pattern Mining for Personalized E-Commerce Recommendations-Reference-Cited by-同舟云学术

OntoCommerce: Incorporating Ontology and Sequential Pattern Mining for Personalized E-Commerce Recommendations

Published:2024 Issue: Volume:12 Page:42329-42342
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Mustafa Ghulam¹^ORCID,Jhamat Naveed Ahmad¹,Arshad Zeeshan¹,Yousaf Nadia¹,Abdal Md. Nazmul²^ORCID,Maray Mohammed³^ORCID,Alqahtani Dokhyl⁴,Merhabi Mohamad Amir⁵^ORCID,Aziz Muhammad Abdul⁶,Ahmad Touseef¹

Affiliation:

1. Department of Information Technology, University of the Punjab, Gujranwala Campus, Gujranwala, Pakistan

2. Department of Computer Science and Engineering, University of Liberal Arts Bangladesh, Dhaka, Bangladesh

3. College of Computer Science and Information Systems, King Khalid University, Abha, Saudi Arabia

4. Electrical Engineering Department, Prince Sattam bin Abdulaziz University, Al-Kharj, Saudi Arabia

5. Management, Marketing, and Entrepreneurship Track, American University of Beirut, Beirut, Lebanon

6. Greenwich Business School, University of Greenwich, London, U.K

Funder

University of the Punjab, Lahore, Pakistan

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10472017.pdf?arnumber=10472017

Reference46 articles.

1. Recommender system application developments: A survey

2. Recommender Systems in Technology Enhanced Learning

3. Customer centric hybrid recommendation system for E-Commerce applications by integrating hybrid sentiment analysis

4. Social Recommendation for Social Networks Using Deep Learning Approach: A Systematic Review

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