Imagen de Portada

Modeling Multi-Hop Semantic Paths for Recommendation in Heterogeneous Information Networks

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zheng, Hongye, Xing, Yue, Zhu, Lipeng, Han, Xu, Du, Junliang, Cui, Wanyu
Formato:	Preprint
Publicado:	2025
Materias:	Information Retrieval Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Unified Representation Learning for Multi-Intent Diversity and Behavioral Uncertainty in Recommender Systems
por: Xu, Wei, et al.
Publicado: (2025)

Contrastive Learning for Cold Start Recommendation with Adaptive Feature Fusion
por: Hu, Jiacheng, et al.
Publicado: (2025)

STARS: Semantic Tokens with Augmented Representations for Recommendation at Scale
por: Chen, Han, et al.
Publicado: (2025)

Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems
por: Liu, Langming, et al.
Publicado: (2025)

Enhancing Recommendation Systems with GNNs and Addressing Over-Smoothing
por: Liu, Wenyi, et al.
Publicado: (2024)

Large Language Model as Universal Retriever in Industrial-Scale Recommender System
por: Jiang, Junguang, et al.
Publicado: (2025)

Towards Scalable Semantic Representation for Recommendation
por: Zhang, Taolin, et al.
Publicado: (2024)

Scaling Generative Recommendations with Context Parallelism on Hierarchical Sequential Transducers
por: Dong, Yue, et al.
Publicado: (2025)

MIARec: Mutual-influence-aware Heterogeneous Network Embedding for Scientific Paper Recommendation
por: Xie, Wenjin, et al.
Publicado: (2025)

Unveiling Vulnerabilities of Contrastive Recommender Systems to Poisoning Attacks
por: Wang, Zongwei, et al.
Publicado: (2023)

DNMDR: Dynamic Networks and Multi-view Drug Representations for Safe Medication Recommendation
por: Liu, Guanlin, et al.
Publicado: (2025)

Calibrated Fusion for Heterogeneous Graph-Vector Retrieval in Multi-Hop QA
por: Bacellar, Andre
Publicado: (2026)

Semantic IDs for Music Recommendation
por: Mei, M. Jeffrey, et al.
Publicado: (2025)

CAST: Modeling Semantic-Level Transitions for Complementary-Aware Sequential Recommendation
por: Zhang, Qian, et al.
Publicado: (2026)

Efficient and Robust Regularized Federated Recommendation
por: Liu, Langming, et al.
Publicado: (2024)

DTN: Deep Multiple Task-specific Feature Interactions Network for Multi-Task Recommendation
por: Bi, Yaowen, et al.
Publicado: (2024)

SIGMA: A Semantic-Grounded Instruction-Driven Generative Multi-Task Recommender at AliExpress
por: Yu, Yang, et al.
Publicado: (2026)

Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning
por: Han, Xiao, et al.
Publicado: (2024)

Adaptive Conditional Expert Selection Network for Multi-domain Recommendation
por: Dong, Kuiyao, et al.
Publicado: (2024)

Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation
por: Zhao, Yuang, et al.
Publicado: (2024)

Better Generalization with Semantic IDs: A Case Study in Ranking for Recommendations
por: Singh, Anima, et al.
Publicado: (2023)

Knowledge Enhanced Multi-Domain Recommendations in an AI Assistant Application
por: Markowitz, Elan, et al.
Publicado: (2023)

EnhancedRL: An Enhanced-State Reinforcement Learning Algorithm for Multi-Task Fusion in Recommender Systems
por: Liu, Peng, et al.
Publicado: (2024)

Recommending Composite Items Using Multi-Level Preference Information: A Joint Interaction Modeling Approach
por: Bi, Xuan, et al.
Publicado: (2026)

Stop Treating Collisions Equally: Qualification-Aware Semantic ID Learning for Recommendation at Industrial Scale
por: Hu, Zheng, et al.
Publicado: (2026)

Masked Multi-Domain Network: Multi-Type and Multi-Scenario Conversion Rate Prediction with a Single Model
por: Ouyang, Wentao, et al.
Publicado: (2024)

Dual-Channel Multiplex Graph Neural Networks for Recommendation
por: Li, Xiang, et al.
Publicado: (2024)

Modeling the Heterogeneous Duration of User Interest in Time-Dependent Recommendation: A Hidden Semi-Markov Approach
por: Zhang, Haidong, et al.
Publicado: (2024)

RankGraph: Unified Heterogeneous Graph Learning for Cross-Domain Recommendation
por: Wu, Renzhi, et al.
Publicado: (2025)

UnifiedRL: A Reinforcement Learning Algorithm Tailored for Multi-Task Fusion in Large-Scale Recommender Systems
por: Liu, Peng, et al.
Publicado: (2024)

End-to-End Semantic ID Generation for Generative Advertisement Recommendation
por: Jiang, Jie, et al.
Publicado: (2026)

SemSR: Semantics aware robust Session-based Recommendations
por: Narwariya, Jyoti, et al.
Publicado: (2025)

Linear-Time Graph Neural Networks for Scalable Recommendations
por: Zhang, Jiahao, et al.
Publicado: (2024)

Retrieve-then-Adapt: Retrieval-Augmented Test-Time Adaptation for Sequential Recommendation
por: Tang, Xing, et al.
Publicado: (2026)

Traceable Drug Recommendation over Medical Knowledge Graphs
por: Lin, Yu, et al.
Publicado: (2025)

FairFS: Addressing Deep Feature Selection Biases for Recommender System
por: Wang, Xianquan, et al.
Publicado: (2026)

Bidding-Aware Retrieval for Multi-Stage Consistency in Online Advertising
por: Liu, Bin, et al.
Publicado: (2025)

Multi-Item-Query Attention for Stable Sequential Recommendation
por: Xu, Mingshi, et al.
Publicado: (2025)

Facet-Aware Multi-Head Mixture-of-Experts Model for Sequential Recommendation
por: Liu, Mingrui, et al.
Publicado: (2024)

Modeling Behavioral Patterns in News Recommendations Using Fuzzy Neural Networks
por: Innerebner, Kevin, et al.
Publicado: (2026)