专题:Recommender Systems and Techniques

This cluster of papers focuses on the advancements in recommender system technologies, including collaborative filtering, matrix factorization, deep learning, content-based recommendation, web mining, context-aware recommender systems, neural networks, user modeling, and trust-aware recommender systems. The papers cover various techniques and methodologies for improving recommendation accuracy and addressing challenges such as cold start problems and privacy concerns.
最新文献
A Multi-timescale Multi-adaptive Dynamical System Approach for Relationship-Specific and Relationship-Independent Adaptivity in Affiliation and Bonding

book-chapter Full Text OpenAlex

DynLLM: When Large Language Models Meet Dynamic Graph-based Recommendation

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GEAR: A Counterfactual Multi-Agent Reinforcement Learning Framework for Strategic Resource Allocation in Game Recommendation Systems

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Domain Adaptation of a BERT Model for Analyzing Job Advertisements at the German Federal Employment Agency

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A Recommender System for University Libraries: Leveraging Book Loan Records with Alternating Least Squares (ALS)

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LEGO: A Lightweight and Efficient Multiple-Attribute Unlearning Framework for Recommender Systems

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Disentangling multi-factor effects via graph contrastive learning for travel recommendation

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Comparison of Large Language Models Supporting the Polish Language in Terms of Faithfulness in Retrieval-Augmented Generation Applications

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RLHF Fine-Tuning of LLMs for Alignment with Implicit User Feedback in Conversational Recommenders

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Maximizing positive influence of live-campaign promotion in live social E-commerce networks

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近5年高被引文献
Graph Neural Networks in Recommender Systems: A Survey

review Full Text OpenAlex 1005 FWCI370.4913328

Proceedings of the 31st ACM International Conference on Multimedia

paratext Full Text OpenAlex 588 FWCI0

A Survey of Graph Neural Networks for Recommender Systems: Challenges, Methods, and Directions

article Full Text OpenAlex 563 FWCI345.73458338

Bias and Debias in Recommender System: A Survey and Future Directions

article Full Text OpenAlex 562 FWCI192.27550195

A Survey of Recommendation Systems: Recommendation Models, Techniques, and Application Fields

article Full Text OpenAlex 553 FWCI207.85513748

Contrastive Learning for Sequential Recommendation

article Full Text OpenAlex 539 FWCI86.52802867

Are Graph Augmentations Necessary?

article Full Text OpenAlex 502 FWCI82.06099851

A systematic review and research perspective on recommender systems

review Full Text OpenAlex 490 FWCI182.39573307

Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning

article Full Text OpenAlex 472 FWCI77.59396835

Communication-efficient federated learning via knowledge distillation

article Full Text OpenAlex 462 FWCI89.67585969