PPA++: Preference Prototype-Aware Learning with Large Language Model for Universal Cross-Domain Recommendation
Abstract While user preferences are important to cross-domain recommendation (CDR), existing methods primarily discover preferences under specific, yet possibly redundant, item features. To this end, we first propose a novel Preference Prototype-Aware (PPA) learning method to quantitatively learn us...
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| Principais autores: | , , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
SpringerOpen
2026-01-01
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| coleção: | Data Science and Engineering |
| Assuntos: | |
| Acesso em linha: | https://doi.org/10.1007/s41019-025-00322-w |
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