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Learning Geographical and Mobility Factors for Mobile Application Recommendation
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-642-00599-2_68openalex-snapshot
Bayesian Non-negative Matrix Factorization
inferredcites →https://doi.org/10.1007/978-3-642-30217-6_36openalex-snapshot
Towards Personalized Context-Aware Recommendation by Mining Context Logs through Topic Models
inferredcites →https://doi.org/10.1007/978-3-642-36516-4_7openalex-snapshot
Understanding Mobile App Usage Patterns Using In-App Advertisements
inferredcites →https://doi.org/10.1109/tcyb.2014.2349954openalex-snapshot
Popularity Modeling for Mobile Apps: A Sequential Approach
inferredcites →https://doi.org/10.1126/science.2983426openalex-snapshot
Rapid and Sensitive Protein Similarity Searches
inferredcites →https://doi.org/10.1145/1961634.1961639openalex-snapshot
Utilizing implicit feedback and context to recommend mobile applications from first use
inferredcites →https://doi.org/10.1145/2532515openalex-snapshot
Mining Mobile User Preferences for Personalized Context-Aware Recommendation
inferredcites →https://doi.org/10.1145/2757513.2757519openalex-snapshot
Exploiting User Context and Network Information for Mobile Application Usage Prediction
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/ett.4728openalex-snapshot
Developing smart city services using intent‐aware recommendation systems: A survey
inferred← citeshttps://doi.org/10.1007/978-3-030-03596-9_29openalex-snapshot
A Weighted Meta-graph Based Approach for Mobile Application Recommendation on Heterogeneous Information Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-65310-1_25openalex-snapshot
A Knowledge Graph Based Approach for Mobile Application Recommendation
inferred← citeshttps://doi.org/10.1007/s00500-020-05397-3openalex-snapshot
Recommendation system based on semantic scholar mining and topic modeling on conference publications
inferred← citeshttps://doi.org/10.1007/s00500-021-05988-8openalex-snapshot
Incorporating contextual information into personalized mobile applications recommendation
inferred← citeshttps://doi.org/10.1016/j.ipm.2020.102416openalex-snapshot
Multi-context embedding based personalized place semantics recognition
inferred← citeshttps://doi.org/10.1016/j.jocs.2018.04.001openalex-snapshot
A privacy-preserving mobile application recommender system based on trust evaluation
inferred← citeshttps://doi.org/10.1080/09540091.2023.2289834openalex-snapshot
Weighted meta-graph based mobile application recommendation through matrix factorisation and neural networks
inferred← citeshttps://doi.org/10.1080/12460125.2023.2198056openalex-snapshot
Motivating change in commuters’ mobility behaviour: Digital nudging for public transportation use
inferred← citeshttps://doi.org/10.1109/access.2019.2918325openalex-snapshot
Enhancing Mobile App User Understanding and Marketing With Heterogeneous Crowdsourced Data: A Review
inferred← citeshttps://doi.org/10.1109/access.2020.3046654openalex-snapshot
A Novel Context-Aware Mobile Application Recommendation Approach Based on Users Behavior Trajectories
inferred← citeshttps://doi.org/10.1109/bigdata47090.2019.9006561openalex-snapshot
DETECT: Deep Trajectory Clustering for Mobility-Behavior Analysis
inferred← citeshttps://doi.org/10.1109/compsac57700.2023.00039openalex-snapshot
Application Recommendation based on Metagraphs: Combining Behavioral and Published Information
inferred← citeshttps://doi.org/10.1109/ijcnn60899.2024.10650932openalex-snapshot
App Recommendation Model Based on Heterogeneous Graph Collaborative Filtering
inferred← citeshttps://doi.org/10.1109/tmc.2020.3012767openalex-snapshot
Which App is Going to Die? A Framework for App Survival Prediction With Multitask Learning
inferred← citeshttps://doi.org/10.1145/3442201openalex-snapshot
Mobile App Cross-Domain Recommendation with Multi-Graph Neural Network
inferred← citeshttps://doi.org/10.1155/2018/8738613openalex-snapshot
A Survey on Machine Learning‐Based Mobile Big Data Analysis: Challenges and Applications
inferred← citeshttps://doi.org/10.1155/2022/1013997openalex-snapshot
Digital Music Recommendation Technology for Music Teaching Based on Deep Learning
inferred← citeshttps://doi.org/10.11606/d.45.2020.tde-13012020-140941openalex-snapshot
Personalização da experiência em museus: aplicação real de um sistema de recomendação
inferred← citeshttps://doi.org/10.48550/arxiv.1808.00803openalex-snapshot
Mobile big data analysis with machine learning
inferred← citeshttps://doi.org/10.48550/arxiv.1812.08304openalex-snapshot
Recommendation System based on Semantic Scholar Mining and Topic modeling: A behavioral analysis of researchers from six conferences
inferred← citeshttps://doi.org/10.48550/arxiv.1909.09551openalex-snapshot
Natural Language Processing via LDA Topic Model in Recommendation Systems
inferred← citeshttps://doi.org/10.48550/arxiv.2003.01351openalex-snapshot
DETECT: Deep Trajectory Clustering for Mobility-Behavior Analysis
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