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2026-10-21, Week 43
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Virual Oral Question and Answer
IEEE/ICACT20260275 Question.5
Questioner: maho.hoshiai@gmail.com    2026-02-13 오전 9:22:01 		IEEE/ICACT20260275 Answer.5
Answer by Auhor yennt@hvnh.edu.vn   2026-02-13 오전 9:22:01
How does HiSeR perform when reviews are noisy or very short? HiSeR remains robust because review information is processed through both sentence-level embeddings and an attention mechanism. We employ Sentence-BERT to generate sentence-level embeddings and the attention layer assigns lower weights to less informative or noisy reviews. Moreover, since review features are combined with ID-based representations, the model does not rely solely on textual content, ensuring stable performance even when reviews are short or noisy.

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