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Proceedings of the 12th ACM Conference on Recommender Systems

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A novel evaluation framework for recommender systems in big data environments
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Federated recommender systems based on deep learning: The experimental comparisons of deep learning algorithms and federated learning aggregation strategies
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Model-agnostic post-hoc explainability for recommender systems
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GitHub marketplace for automation and innovation in software production
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Randomization is all you need: A privacy-preserving federated learning framework for news recommendation
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Sequence recommendation using multi-level self-attention network with gated spiking neural P systems
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Transfer learning in cross-domain sequential recommendation
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Group-aware graph neural networks for sequential recommendation
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Collaborative filtering with representation learning in the frequency domain
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HeteroTempRec: Temporally-aware heterogeneous architecture with sparse block attention for efficient sequential recommendation
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Investigating the lack of diversity in user behavior: The case of musical content on online platforms
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Scalable recommendations using decomposition techniques based on Voronoi diagrams
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Explaining recommender systems fairness and accuracy through the lens of data characteristics
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HGNN: Hyperedge-based graph neural network for MOOC Course Recommendation
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Towards understanding and mitigating unintended biases in language model-driven conversational recommendation
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Keywords-enhanced Contrastive Learning Model for travel recommendation
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Neural Attentive Travel package Recommendation via exploiting long-term and short-term behaviors
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Gating augmented capsule network for sequential recommendation
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Modeling and predicting user preferences with multiple item attributes for sequential recommendations
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On the problem of recommendation for sensitive users and influential items: Simultaneously maintaining interest and diversity
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An ensemble learning framework for click-through rate prediction based on a reinforcement learning algorithm with parameterized actions
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Unifying heterogeneous and homogeneous relations for personalized compatibility modeling
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Attentive preference personalized recommendation with sentence-level explanations
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Leveraging neighborhood session information with dual attentive neural network for session-based recommendation
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A Survey of Privacy Solutions using Blockchain for Recommender Systems: Current Status, Classification and Open Issues
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Fused semantic information and hierarchical attention network for course recommendation
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Preference Networks and Non-Linear Preferences in Group Recommendations
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Learning and Predicting User Pairwise Preferences from Emotions and Gaze Behavior
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Understanding and Predicting User Satisfaction with Conversational Recommender Systems
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FairGap: Fairness-Aware Recommendation via Generating Counterfactual Graph
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Causal Inference in Recommender Systems: A Survey and Future Directions
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Multimodal Pre-training for Sequential Recommendation via Contrastive Learning
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Whom do Explanations Serve? A Systematic Literature Survey of User Characteristics in Explainable Recommender Systems Evaluation
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Review-based Recommender Systems: A Survey of Approaches, Challenges and Future Perspectives
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Semantic Relation Guided Dual-view Contrastive Learning for Session-based Recommendations
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Causal Embeddings for Recommendation: An Extended Abstract
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FAT-DeepFFM: Field Attentive Deep Field-aware Factorization Machine
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Wasserstein Collaborative Filtering for Item Cold-start Recommendation
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Diversity Regularized Interests Modeling for Recommender Systems
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Attentive Flexible Translation Embedding in Top-N Sparse Sequential Recommendations.
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