Rawaa Alatrash

Orcid: 0000-0003-2192-028X

According to our database1, Rawaa Alatrash authored at least 14 papers between 2020 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
Collaborative filtering integrated fine-grained sentiment for hybrid recommender system.
J. Supercomput., March, 2024

Learner Modeling and Recommendation of Learning Resources using Personal Knowledge Graphs.
Proceedings of the 14th Learning Analytics and Knowledge Conference, 2024

2023
Fine-grained Sentiment-enhanced Collaborative Filtering-based Hybrid Recommender System.
J. Web Eng., 2023

Justification vs. Transparency: Why and How Visual Explanations in a Scientific Literature Recommender System.
Inf., 2023

Automatic Construction of Educational Knowledge Graphs: A Word Embedding-Based Approach.
Inf., 2023

Interactive Explanation with Varying Level of Details in an Explainable Scientific Literature Recommender System.
CoRR, 2023

Validation of the EDUSS Framework for Self-Actualization Based on Transparent User Models: A Qualitative Study.
Proceedings of the Adjunct Proceedings of the 31st ACM Conference on User Modeling, 2023

2022
A hybrid E-learning recommendation integrating adaptive profiling and sentiment analysis.
J. Web Semant., 2022

Semantics-Aware Context-Based Learner Modelling Using Normalized PSO for Personalized E-learning.
J. Web Eng., 2022

A Hybrid Recommendation Integrating Semantic Learner Modelling and Sentiment Multi-Classification.
J. Web Eng., 2022

Augmented language model with deep learning adaptation on sentiment analysis for E-learning recommendation.
Cogn. Syst. Res., 2022

What if Interactive Explanation in a Scientific Literature Recommender System.
Proceedings of the 9th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with 16th ACM Conference on Recommender Systems (RecSys 2022), 2022

Learning Channels to Support Interaction and Collaboration in CourseMapper.
Proceedings of the 14th International Conference on Education Technology and Computers, 2022

2020
Semantically enhanced machine learning approach to recommend e-learning content.
Int. J. Electron. Bus., 2020


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