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Proceedings of the Eleventh ACM Conference on Recommender Systems

https://doi.org/10.1145/3109859
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Online Machine Learning in Big Data Streams: Overview
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Recommendation algorithm combining ratings and comments
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Attention-based Frequency-aware Multi-scale Network for Sequential Recommendation
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A graph attention network with contrastive learning for temporal review-based recommendations
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Hyperbolic spatial-temporal network for session-based recommendation
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A Framework for Evaluating Personalized Ranking Systems by Fusing Different Evaluation Measures
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Contextualized Fairness for Recommender Systems in Premium Scenarios
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Deep attention dynamic representation learning networks for recommender system review modeling
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Cross-domain recommendation in MOOCs: A graph capsule network approach with transfer learning
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Unpacking the exploration–exploitation tradeoff on Snapchat: The relationships between users’ exploration–exploitation interests and server log data
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Cruise onboard itinerary planning for multi passengers with service venue capacity and time-window constraints
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Latest trends of security and privacy in recommender systems: A comprehensive review and future perspectives
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Multipath-guided heterogeneous graph neural networks for sequential recommendation
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Similarity matrix enhanced collaborative filtering for e-government recommendation
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Session context data integration to address the cold start problem in e-commerce recommender systems
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Uses of the digital twins concept for energy services, intelligent recommendation systems, and demand side management: A review
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From collaborative filtering to deep learning: Advancing recommender systems with longitudinal data in the financial services industry
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A hierarchical recommendation system for E-commerce using online user reviews
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Incorporating textual reviews in the learning of latent factors for recommender systems
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Rating prediction of recommended item based on review deep learning and rating probability matrix factorization
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IntentRec: Incorporating latent user intent via contrastive alignment for sequential recommendation
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Recommender systems for sensor-based ambient control in academic facilities
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A Deep Hybrid Model for Recommendation by jointly leveraging ratings, reviews and metadata information
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An improved heterogeneous graph convolutional network for job recommendation
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A hybrid approach for artwork recommendation
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Deep click interest network for reranking hotels
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A personalized ranking method based on inverse reinforcement learning in search engines
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A fuzzy approach for natural noise management in group recommender systems
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Graph-based context-aware collaborative filtering
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The recommender canvas: A model for developing and documenting recommender system design
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A personal data store approach for recommender systems: enhancing privacy without sacrificing accuracy
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A compositional model of multi-faceted trust for personalized item recommendation
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DSTP-RNN: A dual-stage two-phase attention-based recurrent neural network for long-term and multivariate time series prediction
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entity2rec: Property-specific knowledge graph embeddings for item recommendation
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An efficient and accurate recommendation strategy using degree classification criteria for item-based collaborative filtering
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Effective and diverse POI recommendations through complementary diversification models
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Geographic Named Entity Recognition and Disambiguation in Mexican News using word embeddings
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Session-based news recommendations using SimRank on multi-modal graphs
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Shared-view and specific-view information extraction for recommendation
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A literature review of implemented recommendation techniques used in Massive Open online Courses
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Entity knowledge transfer-oriented dual-target cross-domain recommendations
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Using consumer feedback from location-based services in PoI recommender systems for people with autism
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Categorization of knowledge graph based recommendation methods and benchmark datasets from the perspectives of application scenarios: A comprehensive survey
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Enhanced graph neural network for session-based recommendation
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A systematic review of value-aware recommender systems
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Recommendations with minimum exposure guarantees: A post-processing framework
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Computing recommendations from free-form text
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T3SRS: Tensor Train Transformer for compressing sequential recommender systems
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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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Accurate multi-interest modeling for sequential recommendation with attention and distillation capsule network
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Semi-global sequential recommendation via EM-like federated training
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Integrating textual reviews into neighbor-based recommender systems
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Unbiased news recommendation model combining time and content
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Hybrid recommendation system for movies using artificial neural network
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Differentially private recommender framework with Dual semi-Autoencoder
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A graph attention network integrated with gated spiking neural P systems for session-based recommendation
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GXNSRec: Multi-behavior sequential recommender based on graph cross networks
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Model-agnostic post-hoc explainability for recommender systems
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Trust in recommender systems: A survey
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A fuzzy model to enhance user profiles in microblogging sites using deep relations
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REHAB-C: Recommendations for Energy HABits Change
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Resource allocation and scheduling in the intelligent edge computing context
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Poverty/investment slow distribution effect analysis based on Hopfield neural network
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Children’s agency by design: Design parameters for personalization in story-making apps
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Intelligent personalized content recommendations based on neural networks
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EARS: Emotion-aware recommender system based on hybrid information fusion
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Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
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Evolving intra-and inter-session graph fusion for next item recommendation
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Deep Latent Factor Model with Hierarchical Similarity Measure for recommender systems
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Sparse online collaborative filtering with dynamic regularization
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Applying landmarks to enhance memory-based collaborative filtering
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A novel hybrid deep recommendation system to differentiate user’s preference and item’s attractiveness
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Click-aware purchase prediction with push at the top
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An endorsement-based trust bootstrapping approach for newcomer cloud services
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DKEN: Deep knowledge-enhanced network for recommender systems
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Dig users’ intentions via attention flow network for personalized recommendation
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Learning to utilize auxiliary reviews for recommendation
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TAERT: Triple-Attentional Explainable Recommendation with Temporal Convolutional Network
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Fusion of latent categorical prediction and sequential prediction for session-based recommendation
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A cost-sensitive temporal-spatial three-way recommendation with multi-granularity decision
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SENGR: Sentiment-Enhanced Neural Graph Recommender
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Towards comprehensive approaches for the rating prediction phase in memory-based collaborative filtering recommender systems
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USST: A two-phase privacy-preserving framework for personalized recommendation with semi-distributed training
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Sequential recommendation: A study on transformers, nearest neighbors and sampled metrics
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Hybrid recommendation by incorporating the sentiment of product reviews
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MGL2Rank: Learning to rank the importance of nodes in road networks based on multi-graph fusion
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Prompt2Rec: Prompt based user and item re-characterizing method for recommendation
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Unveiling user interests: A deep user interest exploration network for sequential location recommendation
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Denoising precedes enrichment: aspect-sentiment-aware graph contrastive distillation network for review-based recommendation
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Dynamic attention-based explainable recommendation with textual and visual fusion
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Investigating the lack of diversity in user behavior: The case of musical content on online platforms
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What makes a review a reliable rating in recommender systems?
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Social influence based community detection in event-based social networks
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Bias-Aware Hierarchical Clustering for detecting the discriminated groups of users in recommendation systems
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Leveraging semantic features for recommendation: Sentence-level emotion analysis
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Investigating and counteracting popularity bias in group recommendations
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Investigating gender fairness of recommendation algorithms in the music domain
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A deep recommendation model of cross-grained sentiments of user reviews and ratings
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Dynamic intent-aware iterative denoising network for session-based recommendation
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A unifying and general account of fairness measurement in recommender systems
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Content recommendation with two-level TransE predictors and interaction-aware embedding enhancement: An information seeking behavior perspective
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Multi-feature fused collaborative attention network for sequential recommendation with semantic-enriched contrastive learning
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MC-RGN: Residual Graph Neural Networks based on Markov Chain for sequential recommendation
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Exploiting dynamic social feedback for session-based recommendation
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QAIE: LLM-based Quantity Augmentation and Information Enhancement for few-shot Aspect-Based Sentiment Analysis
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Combining different metadata views for better recommendation accuracy
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Sequence recommendations for groups: A dynamic approach to balance preferences
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Collaborative knowledge-aware recommendation based on neighborhood negative sampling
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Improved session-based recommender systems using curriculum learning
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An analyses of the effect of using contextual and loyalty features on early purchase prediction of shoppers in e-commerce domain
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Treating adverse effects of blockbuster bias on beyond-accuracy quality of personalized recommendations
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A hybrid recommender system for patron driven library acquisition and weeding
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An enhanced probabilistic fairness-aware group recommendation by incorporating social activeness
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When services computing meets blockchain: Challenges and opportunities
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A/B testing: A systematic literature review
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WE-Rec: A fairness-aware reciprocal recommendation based on Walrasian equilibrium
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An encoder–decoder switch network for purchase prediction
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An OWA-based hierarchical clustering approach to understanding users’ lifestyles
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Memory-aware gated factorization machine for top-N recommendation
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Hierarchical text interaction for rating prediction
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Neural graph personalized ranking for Top-N Recommendation
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CaSe4SR: Using category sequence graph to augment session-based recommendation
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Hybrid ecommerce recommendation model incorporating product taxonomy and folksonomy
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Enhanced review-based rating prediction by exploiting aside information and user influence
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Learning product representations for generating reviews for cold products
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Post-hoc recommendation explanations through an efficient exploitation of the DBpedia category hierarchy
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Inductive conformal recommender system
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Modeling and predicting user preferences with multiple item attributes for sequential recommendations
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Privacy-preserving Federated Learning and its application to natural language processing
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On the problem of recommendation for sensitive users and influential items: Simultaneously maintaining interest and diversity
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SSE4Rec: Sequential recommendation with subsequence extraction
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SRM-TGA: A session-based recommendation model supported by temporal graph attention
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Dual space multi-granular model for multi-interest sequential recommendation
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Modeling High-order relationships and dynamic preferences for group recommendation
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Bayesian pairwise learning to rank via one-class collaborative filtering
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Hybrid neural recommendation with joint deep representation learning of ratings and reviews
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Robust multi-view clustering via inter-and-intra-view low rank fusion
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Knowledge graph based natural language generation with adapted pointer-generator networks
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Exploiting geographical-temporal awareness attention for next point-of-interest recommendation
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Matrix factorization with heterogeneous multiclass preference context
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HTDA: Hierarchical time-based directional attention network for sequential user behavior modeling
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Visual content-enhanced sequential recommendation with feature-level attention
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DSGNN: A dynamic and static intentions integrated graph neural network for session-based recommendation
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A survey of recommender systems with multi-objective optimization
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TransMKR: Translation-based knowledge graph enhanced multi-task point-of-interest recommendation
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Graph neural networks with global noise filtering for session-based recommendation
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Session-based recommendation with temporal convolutional network to balance numerical gaps
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Enhancing collaborative translational metric learning with causal graph network
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Enhancing effective connection with link prediction for session-based recommendation
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Frequency-sensitive diffusion model for personalized sequential recommendation
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NeuO: Exploiting the sentimental bias between ratings and reviews with neural networks
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A multi-agent reinforcement learning framework for cross-domain sequential recommendation
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Cost-Based attraction recommendation for tour operators under stochastic demand
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Topic modelling for routine discovery from egocentric photo-streams
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DeepLTRS: A deep latent recommender system based on user ratings and reviews
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Analysing exposure diversity in collaborative recommender systems—Entropy fusion approach
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An online reinforcement learning approach to quality-cost-aware task allocation for multi-attribute social sensing
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Mining Implicit Behavioral Patterns via Attention Networks for Sequential Recommendation
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An autoencoder-based deep learning model for solving the sparsity issues of Multi-Criteria Recommender System
inferred← citeshttps://doi.org/10.1016/j.simpa.2023.100606openalex-snapshot
CAPRI: Context-aware point-of-interest recommendation framework
inferred← citeshttps://doi.org/10.1016/j.techfore.2023.122343openalex-snapshot
How should the results of artificial intelligence be explained to users? - Research on consumer preferences in user-centered explainable artificial intelligence
inferred← citeshttps://doi.org/10.1038/s41598-025-08256-zopenalex-snapshot
Efficient federated graph aggregation for privacy-preserving GNN-based session recommendation
inferred← citeshttps://doi.org/10.1109/icmiii62623.2024.00166openalex-snapshot
Enhancing Sentiment Analysis through Text Classification Using Data Mining Approach
inferred← citeshttps://doi.org/10.1117/12.3058778openalex-snapshot
Graph convolution recommendation system based on knowledge graph
inferred← citeshttps://doi.org/10.1145/3397271.3401051openalex-snapshot
Fairness-Aware Explainable Recommendation over Knowledge Graphs
inferred← citeshttps://doi.org/10.1145/3404835.3462966openalex-snapshot
Towards Personalized Fairness based on Causal Notion
inferred← citeshttps://doi.org/10.1145/3442381.3449866openalex-snapshot
User-oriented Fairness in Recommendation
inferred← citeshttps://doi.org/10.1145/3447548.3467160openalex-snapshot
SizeFlags: Reducing Size and Fit Related Returns in Fashion E-Commerce
inferred← citeshttps://doi.org/10.1145/3460231.3470935openalex-snapshot
RecSys in HR: Workshop on Recommender Systems for Human Resources
inferred← citeshttps://doi.org/10.1145/3460231.3478859openalex-snapshot
Do Users Appreciate Explanations of Recommendations? An Analysis in the Movie Domain
inferred← citeshttps://doi.org/10.1145/3472306.3478358openalex-snapshot
Informing the Design of a News Chatbot
inferred← citeshttps://doi.org/10.1145/3477495.3531973openalex-snapshot
Explainable Fairness in Recommendation
inferred← citeshttps://doi.org/10.1145/3539813.3545142openalex-snapshot
The Bandwagon Effect: Not Just Another Bias
inferred← citeshttps://doi.org/10.1145/3673234openalex-snapshot
Aspect-Enhanced Explainable Recommendation with Multi-modal Contrastive Learning
inferred← citeshttps://doi.org/10.1145/3698877openalex-snapshot
Explaining Recommendation Fairness from a User/Item Perspective
inferred← citeshttps://doi.org/10.1145/3700445openalex-snapshot
Advancing Session-Based Recommendations with Atten-Mixer+: Dynamic and Adaptive Multi-Level Intent Mining
inferred← citeshttps://doi.org/10.1145/3700890openalex-snapshot
A Survey on Intent-aware Recommender Systems
inferred← citeshttps://doi.org/10.1145/3701988openalex-snapshot
Disentangled Dynamic Graph Attention Network for Out-of-Distribution Sequential Recommendation
inferred← citeshttps://doi.org/10.1145/3708883openalex-snapshot
Thoroughly Modeling Multi-domain Pre-trained Recommendation as Language
inferred← citeshttps://doi.org/10.1145/3709138openalex-snapshot
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services
inferred← citeshttps://doi.org/10.1145/3715099openalex-snapshot
LLMCDSR: Enhancing Cross-Domain Sequential Recommendation with Large Language Models
inferred← citeshttps://doi.org/10.1145/3726302.3730017openalex-snapshot
Killing Two Birds with One Stone: Unifying Retrieval and Ranking with a Single Generative Recommendation Model
inferred← citeshttps://doi.org/10.1145/3742421openalex-snapshot
Review-based Recommender Systems: A Survey of Approaches, Challenges and Future Perspectives
inferred← citeshttps://doi.org/10.1145/3749106openalex-snapshot
A Fair Enhanced Bayesian Personalized Ranking Using Adversarial Learning
inferred← citeshttps://doi.org/10.1145/3754459openalex-snapshot
SM-RS 2.0: User-perceived Qualities of Single- and Multi-Objective Recommender Systems
inferred← citeshttps://doi.org/10.1145/3772273openalex-snapshot
Review of Explainable Graph-Based Recommender Systems
inferred← citeshttps://doi.org/10.11606/d.3.2022.tde-26072023-084455openalex-snapshot
Geração de explicações para sistemas de recomendação conversacionais baseados em embeddings de conhecimento.
inferred← citeshttps://doi.org/10.11606/d.55.2021.tde-23062021-105306openalex-snapshot
Exploiting Inter-session Dynamics for Long Intra-Session Sequences of Interactions with Deep Reinforcement Learning for Session-Aware Recommendation
inferred← citeshttps://doi.org/10.11606/t.55.2020.tde-04022020-154009openalex-snapshot
Enhancing recommender systems by enrichment with pre- processing approaches supported by users\' feedback
inferred← citeshttps://doi.org/10.1177/0165551521999801openalex-snapshot
Personalised attraction recommendation for enhancing topic diversity and accuracy
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2824593/v1openalex-snapshot
A Serendipity Recommendation Method for Book Categories Using BERT
inferred← citeshttps://doi.org/10.21203/rs.3.rs-5304404/v1openalex-snapshot
Contrastive Learning-optimized recommendation data to Construct a Language Model Recommendation
inferred← citeshttps://doi.org/10.25236/ajcis.2022.051413openalex-snapshot
Design of collaborative filtering recommendation algorithm combining time weight and reward and punishment factors
inferred← citeshttps://doi.org/10.32657/10356/164474openalex-snapshot
Transferable and curious AI in sequential recommendation
inferred← citeshttps://doi.org/10.32657/10356/173690openalex-snapshot
Impact of temporal context on recommender systems along global timeline
inferred← citeshttps://doi.org/10.52396/justc-2022-0100openalex-snapshot
LightAD: accelerating AutoDebias with adaptive sampling
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