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E-Learning Course Recommender System Using Collaborative Filtering Models

https://doi.org/10.3390/electronics12010157

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-45183-7_11openalex-snapshot

Unsupervised Deep Collaborative Filtering Recommender System for E-Learning Platforms

inferredcites →https://doi.org/10.1007/978-3-030-66840-2_21openalex-snapshot

A Comparative Study Between K-Nearest Neighbors and K-Means Clustering Techniques of Collaborative Filtering in e-Learning Environment

inferredcites →https://doi.org/10.1007/978-3-031-01942-5_36openalex-snapshot

E-learning Recommendation Systems: A Literature Review

inferredcites →https://doi.org/10.1007/978-3-319-11071-4_14openalex-snapshot

A New User Similarity Computation Method for Collaborative Filtering Using Artificial Neural Network

inferredcites →https://doi.org/10.1007/978-981-13-7403-6_11openalex-snapshot

Supervised Classification Algorithms in Machine Learning: A Survey and Review

inferredcites →https://doi.org/10.1007/978-981-15-8744-3_5openalex-snapshot

Personalization in Education Using Recommendation System: An Overview

inferredcites →https://doi.org/10.1007/978-981-33-6893-4_9openalex-snapshot

E-learning Recommendation System Based on Cloud Computing

inferredcites →https://doi.org/10.1007/s10462-022-10135-2openalex-snapshot

A review of deep learning-based recommender system in e-learning environments

inferredcites →https://doi.org/10.1007/s10586-017-1560-6openalex-snapshot

A collaborative filtering recommendation algorithm based on the influence sets of e-learning group’s behavior

inferredcites →https://doi.org/10.1007/s10639-019-10063-9openalex-snapshot

A systematic review: machine learning based recommendation systems for e-learning

inferredcites →https://doi.org/10.1007/s10639-022-10914-yopenalex-snapshot

ERSDO: E-learning Recommender System based on Dynamic Ontology

inferredcites →https://doi.org/10.1007/s10639-022-10966-0openalex-snapshot

Smart Learning Objects Retrieval for E-Learning with Contextual Recommendation based on Collaborative Filtering

inferredcites →https://doi.org/10.1007/s11423-010-9155-4openalex-snapshot

Learning materials recommendation using good learners’ ratings and content-based filtering

inferredcites →https://doi.org/10.1016/j.caeai.2022.100047openalex-snapshot

A systematic review of ontology use in E-Learning recommender system

inferredcites →https://doi.org/10.1016/j.eij.2021.05.003openalex-snapshot

Enabling recommendation system architecture in virtualized environment for e-learning

inferredcites →https://doi.org/10.1016/j.eswa.2016.09.040openalex-snapshot

Collaborative filtering and deep learning based recommendation system for cold start items

inferredcites →https://doi.org/10.1016/j.knosys.2009.01.008openalex-snapshot

Collaborative filtering adapted to recommender systems of e-learning

inferredcites →https://doi.org/10.1016/j.knosys.2022.109934openalex-snapshot

Semantic-enhanced neural collaborative filtering models in recommender systems

inferredcites →https://doi.org/10.1016/j.procs.2019.04.166openalex-snapshot

Social Collaborative Filtering Approach for Recommending Courses in an E-learning Platform

inferredcites →https://doi.org/10.1080/23311916.2021.2022568openalex-snapshot

Knowledge-based recommendation system using semantic web rules based on Learning styles for MOOCs

inferredcites →https://doi.org/10.1109/csse.2008.305openalex-snapshot

E-learning Recommendation System

inferredcites →https://doi.org/10.1109/icacci.2013.6637502openalex-snapshot

Contextual information based recommender system using Singular Value Decomposition

inferredcites →https://doi.org/10.1109/icect.2005.102openalex-snapshot

Using Singular Value Decomposition Approximation for Collaborative Filtering

inferredcites →https://doi.org/10.1109/itsim.2010.5561329openalex-snapshot

A proposed semantic recommendation system for e-learning: A rule and ontology based e-learning recommendation system

inferredcites →https://doi.org/10.1109/tlt.2021.3058644openalex-snapshot

Evaluating the Quality of Learning Resources: A Learnersourcing Approach

inferredcites →https://doi.org/10.1109/wkdd.2009.132openalex-snapshot

Combining Singular Value Decomposition and Item-based Recommender in Collaborative Filtering

inferredcites →https://doi.org/10.1142/s0219622021500619openalex-snapshot

Pointer-Based Item-to-Item Collaborative Filtering Recommendation System Using a Machine Learning Model

inferredcites →https://doi.org/10.1155/2022/1010122openalex-snapshot

The Construction of Accurate Recommendation Model of Learning Resources of Knowledge Graph under Deep Learning

inferredcites →https://doi.org/10.14742/ajet.1041openalex-snapshot

Measuring learner's performance in e-learning recommender systems

inferredcites →https://doi.org/10.3233/kes-190402openalex-snapshot

Recommender system using item based collaborative filtering (CF) and K-means

inferredcites →https://doi.org/10.3390/data6020018openalex-snapshot

The State of the Art in Methodologies of Course Recommender Systems—A Review of Recent Research

inferredcites →https://doi.org/10.3390/math9020197openalex-snapshot

Design and Analysis of a Cluster-Based Intelligent Hybrid Recommendation System for E-Learning Applications

inferredcites →https://doi.org/10.4018/978-1-5225-2148-8.ch011openalex-snapshot

Recommender System

inferredcites →https://doi.org/10.5120/ijca2016908821openalex-snapshot

Survey on Recommendation System

inferredcites →https://doi.org/10.5120/ijca2017916055openalex-snapshot

Use of Deep Learning in Modern Recommendation System: A Summary of Recent Works

What points at this work

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Social Recommender Systems in E-Learning Environments: A Literature Review

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Personalized E-Learning Recommender System Using Machine Learning

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Optimizing Recommendation Systems in E-Learning: Synergistic Integration of Lang Chain, GPT Models, and Retrieval Augmented Generation (RAG)

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inferred← citeshttps://doi.org/10.2991/978-94-6463-417-4_23openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/app13106201openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/app14093672openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/electronics12040809openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/electronics12071593openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/electronics12194017openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/en16031437openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/info14090505openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/info15100660openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/info15120803openalex-snapshot

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inferred← citeshttps://doi.org/10.36227/techrxiv.175203757.71749390/v1openalex-snapshot

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inferred← citeshttps://doi.org/10.36227/techrxiv.175234472.20931823/v1openalex-snapshot

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inferred← citeshttps://doi.org/10.36227/techrxiv.175234481.17023402/v1openalex-snapshot

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inferred← citeshttps://doi.org/10.3991/ijep.v14i1.47109openalex-snapshot

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inferred← citeshttps://doi.org/10.3991/itdaf.v3i4.59211openalex-snapshot

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inferred← citeshttps://doi.org/10.4018/ijitsa.395338openalex-snapshot

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inferred← citeshttps://doi.org/10.46729/ijstm.v4i6.1009openalex-snapshot

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inferred← citeshttps://doi.org/10.54692/lgurjcsit.2024.084613openalex-snapshot

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inferred← citeshttps://doi.org/10.62411/faith.3048-3719-303openalex-snapshot

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inferred← citeshttps://doi.org/10.62411/jcta.12603openalex-snapshot

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inferred← citeshttps://doi.org/10.70675/0fd09746zc195z4bbdzb16ezfe80df8dce3fopenalex-snapshot

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