Predicting User Interest Using Hierarchical-Based Clustering for Recommender Systems-Reference-Cited by-同舟云学术

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Predicting User Interest Using Hierarchical-Based Clustering for Recommender Systems

Published:2023-11-10 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference of Computer Science and Information Technology (ICOSNIKOM)
language:
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Author:

Zarei M. Alizadeh¹,Hosseini F.²,Nickfarjam A. M.³,Xiao T.⁴

Affiliation:

1. Islamic Azad University of Kashan,Faculty of Electrical and Computer Engineering,Department of Computer Engineering,Kashan,Iran

2. University of North Texas,Department of Computer Science,Denton,Texas,USA

3. Kashan University of Medical Sciences,Department of Health Information Management and Technology,Kashan,Iran

4. University of North Texas,Department of Information Science,Denton,Texas,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10364336/10364339/10364498.pdf?arnumber=10364498

Reference11 articles.

1. A review on deep learning for recommender systems: challenges and remedies

2. Movie Recommendation using Collaborative filtering and Content-based Filtering Approach

3. Content-based group recommender systems: A general taxonomy and further improvements

4. Assessing the Performance of Recommender Systems with MovieTweetings and MovieLens Datasets

5. Presentation of a recommender system with ensemble learning and graph embedding: a case on MovieLens

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