Papers by Abdulla Alshabanah

2 papers
On Using Arabic Language Dialects in Recommendation Systems (2025.findings-naacl)

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Challenge: Using natural language processing (NLP) to analyze user reviews in recommendation systems is unexplored.
Approach: They propose to integrate Arabic dialects as a signal in recommendation systems by using explicit and implicit approaches.
Outcome: The proposed approach improves recommendation performance and encourages further research in the Arab multicultural world.
Mind the Dialect: NLP Advancements Uncover Fairness Disparities for Arabic Users in Recommendation Systems (2025.findings-emnlp)

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Challenge: a recent study shows that recommendation systems can exhibit unfair behavior when performance varies across users . the authors highlight the intersection of NLP and recommendation system research .
Approach: They investigate fairness disparities in recommendation quality among Arabic-speaking users . arab-speaking people's dialectal diversity is underrepresented in recommendation system research .
Outcome: The authors highlight the intersection of NLP and recommendation systems . their findings highlight the broader social impact of N.

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