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Mobile App Cross-Domain Recommendation with Multi-Graph Neural Network
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Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-0-387-85820-3openalex-snapshot
Recommender Systems Handbook
inferredcites →https://doi.org/10.1016/j.crma.2012.03.014openalex-snapshot
Multiple-gradient descent algorithm (MGDA) for multiobjective optimization
inferredcites →https://doi.org/10.1109/access.2019.2918325openalex-snapshot
Enhancing Mobile App User Understanding and Marketing With Heterogeneous Crowdsourced Data: A Review
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/mis.2017.52openalex-snapshot
Learning Geographical and Mobility Factors for Mobile Application Recommendation
inferredcites →https://doi.org/10.1109/tkde.2018.2849727openalex-snapshot
A Survey on Network Embedding
inferredcites →https://doi.org/10.1109/tmc.2018.2868933openalex-snapshot
CompetitiveBike: Competitive Analysis and Popularity Prediction of Bike-Sharing Apps Using Multi-Source Data
inferredcites →https://doi.org/10.1109/tnnls.2020.2978386openalex-snapshot
A Comprehensive Survey on Graph Neural Networks
inferredcites →https://doi.org/10.1109/tpami.2013.50openalex-snapshot
Representation Learning: A Review and New Perspectives
inferredcites →https://doi.org/10.1137/1.9781611975673.74openalex-snapshot
Multi-dimensional Graph Convolutional Networks
inferredcites →https://doi.org/10.1145/1273496openalex-snapshot
Proceedings of the 24th international conference on Machine learning
inferredcites →https://doi.org/10.1145/2484028.2484035openalex-snapshot
Addressing cold-start in app recommendation
inferredcites →https://doi.org/10.1145/2623330.2623705openalex-snapshot
Mobile app recommendations with security and privacy awareness
inferredcites →https://doi.org/10.1145/2684822.2685322openalex-snapshot
Personalized Mobile App Recommendation
inferredcites →https://doi.org/10.1145/2959100.2959190openalex-snapshot
Deep Neural Networks for YouTube Recommendations
inferredcites →https://doi.org/10.1145/3219819.3219855openalex-snapshot
Learning and Transferring IDs Representation in E-commerce
inferredcites →https://doi.org/10.1145/3219819.3219869openalex-snapshot
Billion-scale Commodity Embedding for E-commerce Recommendation in Alibaba
inferredcites →https://doi.org/10.1145/3219819.3219885openalex-snapshot
Real-time Personalization using Embeddings for Search Ranking at Airbnb
inferredcites →https://doi.org/10.1145/3219819.3219890openalex-snapshot
Graph Convolutional Neural Networks for Web-Scale Recommender Systems
inferredcites →https://doi.org/10.1145/3287060openalex-snapshot
Modeling and Forecasting the Popularity Evolution of Mobile Apps
inferredcites →https://doi.org/10.1145/3289600.3290973openalex-snapshot
Solving the Sparsity Problem in Recommendations via Cross-Domain Item Embedding Based on Co-Clustering
inferredcites →https://doi.org/10.24963/ijcai.2017/343openalex-snapshot
Cross-Domain Recommendation: An Embedding and Mapping Approach
inferredcites →https://doi.org/10.24963/ijcai.2018/516openalex-snapshot
A Deep Framework for Cross-Domain and Cross-System Recommendations
inferredcites →https://doi.org/10.48550/arxiv.1709.05584openalex-snapshot
Representation Learning on Graphs: Methods and Applications
inferredcites →https://doi.org/10.5281/zenodo.20695702openalex-snapshot
RhizoDB: A Bounded Activation-Flow Architecture for Graph-Based Memory Systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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MAPTRec: a multi-view attention framework for heterogeneous cross-domain recommendation
inferred← citeshttps://doi.org/10.1016/j.dajour.2024.100518openalex-snapshot
A systematic review of the literature on deep learning approaches for cross-domain recommender systems
inferred← citeshttps://doi.org/10.1016/j.engappai.2023.105974openalex-snapshot
Semantic similarity for mobile application recommendation under scarce user data
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.121564openalex-snapshot
DDHCN: Dual decoder Hyperformer convolutional network for Downstream-Adaptable user representation learning on app usage
inferred← citeshttps://doi.org/10.1016/j.eswa.2025.128765openalex-snapshot
A personalized active learning strategy with enhanced user satisfaction for recommender systems
inferred← citeshttps://doi.org/10.1108/dta-03-2023-0101openalex-snapshot
AsCDPR: a novel framework for ratings and personalized preference hotel recommendation using cross-domain and aspect-based features
inferred← citeshttps://doi.org/10.1109/access.2023.3323353openalex-snapshot
Deep Learning-Based Recommendation System: Systematic Review and Classification
inferred← citeshttps://doi.org/10.1109/aiars63200.2024.00046openalex-snapshot
E-Commerce Big Data Analysis and User Behavior Prediction Algorithm Based on Deep Learning
inferred← citeshttps://doi.org/10.1109/comst.2022.3163176openalex-snapshot
Smartphone App Usage Analysis: Datasets, Methods, and Applications
inferred← citeshttps://doi.org/10.1109/icnisc57059.2022.00135openalex-snapshot
Graph Neural Networks based Recommendation Methods in Different Scenarios: A Survey
inferred← citeshttps://doi.org/10.1109/iwcmc58020.2023.10182890openalex-snapshot
Four-level knowledge graph contrastive learning structure for smart-phone application recommendation
inferred← citeshttps://doi.org/10.1109/jiot.2022.3194726openalex-snapshot
CrowdHMT: Crowd Intelligence With the Deep Fusion of Human, Machine, and IoT
inferred← citeshttps://doi.org/10.1109/tai.2024.3443028openalex-snapshot
An Approach for Privacy-Aware Mobile App Package Recommendation
inferred← citeshttps://doi.org/10.1109/tnse.2025.3604790openalex-snapshot
AttrAppGen: User Attribute-Aware App Usage Trace Generation With Large Language Models
inferred← citeshttps://doi.org/10.1145/3539618.3591969openalex-snapshot
Curriculum Modeling the Dependence among Targets with Multi-task Learning for Financial Marketing
inferred← citeshttps://doi.org/10.1145/3568683openalex-snapshot
Characterizing and Forecasting Urban Vibrancy Evolution: A Multi-View Graph Mining Perspective
inferred← citeshttps://doi.org/10.1145/3604615openalex-snapshot
Sequential and Graphical Cross-Domain Recommendations with a Multi-View Hierarchical Transfer Gate
inferred← citeshttps://doi.org/10.1145/3630259openalex-snapshot
Adaptive Adversarial Contrastive Learning for Cross-Domain Recommendation
inferred← citeshttps://doi.org/10.1145/3640457.3688101openalex-snapshot
Touch the Core: Exploring Task Dependence Among Hybrid Targets for Recommendation
inferred← citeshttps://doi.org/10.1145/3653976openalex-snapshot
Dual Homogeneity Hypergraph Motifs with Cross-view Contrastive Learning for Multiple Social Recommendations
inferred← citeshttps://doi.org/10.1145/3663364openalex-snapshot
A Survey on Variational Autoencoders in Recommender Systems
inferred← citeshttps://doi.org/10.32604/iasc.2022.022266openalex-snapshot
Quality Prediction of Wearable Apps in the Google Play Store
inferred← citeshttps://doi.org/10.3390/app13074389openalex-snapshot
An Image Recommendation Algorithm Based on Target Alternating Attention and User Affiliation Network
inferred← citeshttps://doi.org/10.4018/irmj.345360openalex-snapshot
A Comment Aspect-Level User Preference Transfer Model for Cross-Domain Recommendations
inferred← citeshttps://doi.org/10.54254/2755-2721/2/20220577openalex-snapshot
Comprehensive Analysis for Intelligent Recommendation on Mobile Applications
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