CD-LLMCARS: Cross Domain Fine-Tuned Large Language Model for Context-Aware Recommender Systems

Recommender systems are essential for providing personalized content across various platforms. However, traditional systems often struggle with limited information, known as the cold start problem, and with accurately interpreting a user's comprehensive preferences, referred to as context. The...

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Veröffentlicht in:	IEEE open journal of the Computer Society Jg. 6; S. 49 - 59
Hauptverfasser:	Cheema, Adeel Ashraf, Sarfraz, Muhammad Shahzad, Habib, Usman, Zaman, Qamar Uz, Boonchieng, Ekkarat
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Collaborative filtering Context Context modeling context-aware recommeder systems (CARS) cross-domain recommender systems (CDRS) History Large language models large language models (LLMs) prompt engineering Recommender systems Reviews Training Tuning User experience
ISSN:	2644-1268, 2644-1268
Online-Zugang:	Volltext
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