Learning-based models for building user profiles for personalized information access
<|reference_start|>Learning-based models for building user profiles for personalized information access: This study contributes to the literature by considering the difference in vocabulary used to express document content and information needs. Users are integrated into all research phases in order to provide them with relevant information adapted to their context and their preferences meeting their precise needs. To better express document content and information during this phase, deep learning models are employed to learn complex representations of documents and queries. These models can capture hierarchical, sequential, or attention-based patterns in textual data.<|reference_end|>
@article{hidri2024learning-based,
    title={Learning-based models for building user profiles for personalized
  information access},
    author={Minyar Sassi Hidri},
    journal={Interdisciplinary Journal of Information, Knowledge, and
  Management, Volume 19, 2024, pp. 010},
    year={2024},
    doi={10.28945/5275},
    archivePrefix={arXiv},
    eprint={2405.15791},
    primaryClass={cs.IR}
}