On the public citation graph
Attentive Aspect Modeling for Review-Aware Recommendation
0 signed · 171 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-031-02165-7openalex-snapshot
Neural Network Methods for Natural Language Processing
inferredcites →https://doi.org/10.1007/978-3-642-38844-6_1openalex-snapshot
Opinion-Driven Matrix Factorization for Rating Prediction
inferredcites →https://doi.org/10.1007/s11257-015-9155-5openalex-snapshot
Recommender systems based on user reviews: the state of the art
inferredcites →https://doi.org/10.1016/j.is.2012.03.001openalex-snapshot
Improving the quality of predictions using textual information in online user reviews
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/tip.2017.2710635openalex-snapshot
Coherent Semantic-Visual Indexing for Large-Scale Image Retrieval in the Cloud
inferredcites →https://doi.org/10.1109/tkde.2016.2598740openalex-snapshot
Integrating Topic and Latent Factors for Scalable Personalized Review-based Rating Prediction
inferredcites →https://doi.org/10.1109/tkde.2018.2831682openalex-snapshot
NAIS: Neural Attentive Item Similarity Model for Recommendation
inferredcites →https://doi.org/10.1145/1835449.1835676openalex-snapshot
Learning to rank for information retrieval
inferredcites →https://doi.org/10.1145/1864708.1864721openalex-snapshot
Performance of recommender algorithms on top-n recommendation tasks
inferredcites →https://doi.org/10.1145/2507157.2507163openalex-snapshot
Hidden factors and hidden topics
inferredcites →https://doi.org/10.1145/2600428.2609579openalex-snapshot
Explicit factor models for explainable recommendation based on phrase-level sentiment analysis
inferredcites →https://doi.org/10.1145/2661829.2662059openalex-snapshot
Collaborative Filtering Incorporating Review Text and Co-clusters of Hidden User Communities and Item Groups
inferredcites →https://doi.org/10.1145/2911451.2911549openalex-snapshot
Learning to Rank Features for Recommendation over Multiple Categories
inferredcites →https://doi.org/10.1145/2960408openalex-snapshot
Ranking-Oriented Collaborative Filtering
inferredcites →https://doi.org/10.1145/3017429openalex-snapshot
Cross-Platform App Recommendation by Jointly Modeling Ratings and Texts
inferredcites →https://doi.org/10.1145/3018661.3018665openalex-snapshot
Joint Deep Modeling of Users and Items Using Reviews for Recommendation
inferredcites →https://doi.org/10.1145/3038912.3052569openalex-snapshot
Neural Collaborative Filtering
inferredcites →https://doi.org/10.1145/3077136.3080777openalex-snapshot
Neural Factorization Machines for Sparse Predictive Analytics
inferredcites →https://doi.org/10.1145/3077136.3080797openalex-snapshot
Attentive Collaborative Filtering
inferredcites →https://doi.org/10.1145/3132847.3132892openalex-snapshot
Joint Representation Learning for Top-N Recommendation with Heterogeneous Information Sources
inferredcites →https://doi.org/10.1145/3178876.3186070openalex-snapshot
Neural Attentional Rating Regression with Review-level Explanations
inferredcites →https://doi.org/10.1145/3178876.3186072openalex-snapshot
Scalable Supervised Discrete Hashing for Large-Scale Search
inferredcites →https://doi.org/10.1145/3178876.3186145openalex-snapshot
Aspect-Aware Latent Factor Model
inferredcites →https://doi.org/10.1145/3209978.3209991openalex-snapshot
Collaborative Memory Network for Recommendation Systems
inferredcites →https://doi.org/10.1145/3209978.3209998openalex-snapshot
Attentive Group Recommendation
inferredcites →https://doi.org/10.1145/3240508.3240541openalex-snapshot
Multi-modal Preference Modeling for Product Search
inferredcites →https://doi.org/10.1145/3243652openalex-snapshot
Transfer to Rank for Heterogeneous One-Class Collaborative Filtering
inferredcites →https://doi.org/10.1145/3289600.3290982openalex-snapshot
Social Attentional Memory Network
inferredcites →https://doi.org/10.1145/361219.361220openalex-snapshot
A vector space model for automatic indexing
inferredcites →https://doi.org/10.1561/1500000016openalex-snapshot
Learning to Rank for Information Retrieval
inferredcites →https://doi.org/10.1561/9781601982452openalex-snapshot
Learning to Rank for Information Retrieval
inferredcites →https://doi.org/10.1609/aaai.v32i1.11685openalex-snapshot
Exploiting Emotion on Reviews for Recommender Systems
inferredcites →https://doi.org/10.2200/s00762ed1v01y201703hlt037openalex-snapshot
Neural Network Methods for Natural Language Processing
inferredcites →https://doi.org/10.24963/ijcai.2017/435openalex-snapshot
Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks
inferredcites →https://doi.org/10.24963/ijcai.2017/674openalex-snapshot
User-Based Opinion-based Recommendation
inferredcites →https://doi.org/10.24963/ijcai.2018/521openalex-snapshot
A^3NCF: An Adaptive Aspect Attention Model for Rating Prediction
inferredcites →https://doi.org/10.48550/arxiv.1205.2618openalex-snapshot
BPR: Bayesian Personalized Ranking from Implicit Feedback
inferredcites →https://doi.org/10.48550/arxiv.1301.3781openalex-snapshot
Efficient Estimation of Word Representations in Vector Space
inferredcites →https://doi.org/10.48550/arxiv.1405.4053openalex-snapshot
Distributed Representations of Sentences and Documents
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1605.07722openalex-snapshot
Yum-me: A Personalized Nutrient-based Meal Recommender System
inferredcites →https://doi.org/10.48550/arxiv.1802.07938openalex-snapshot
Aspect-Aware Latent Factor Model: Rating Prediction with Ratings and Reviews
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-1-0716-2197-4_5openalex-snapshot
Deep Learning for Recommender Systems
inferred← citeshttps://doi.org/10.1007/978-3-030-73200-4_1openalex-snapshot
Gated Sequential Recommendation System with Social and Textual Information Under Dynamic Contexts
inferred← citeshttps://doi.org/10.1007/978-3-030-76520-0_25openalex-snapshot
Aspect-Based Recommendation Model for Fashion Merchandising
inferred← citeshttps://doi.org/10.1007/978-3-030-92273-3_49openalex-snapshot
AGRP: A Fused Aspect-Graph Neural Network for Rating Prediction
inferred← citeshttps://doi.org/10.1007/978-3-031-20868-3_4openalex-snapshot
Pattern Matching and Information-Aware Between Reviews and Ratings for Recommendation
inferred← citeshttps://doi.org/10.1007/978-3-031-35891-3_18openalex-snapshot
Evaluating Explainable AI (XAI) in Terms of User Gender and Educational Background
inferred← citeshttps://doi.org/10.1007/978-3-031-83472-1_21openalex-snapshot
A Supervised Contrastive Learning Framework for Aspect-Based Recommendations
inferred← citeshttps://doi.org/10.1007/978-981-19-4453-6_5openalex-snapshot
An Improved Recommendation System with Aspect-Based Sentiment Analysis
inferred← citeshttps://doi.org/10.1007/978-981-92-3391-5_47openalex-snapshot
DGAD: A Dual-Graph Framework with Aspect-Aware and Dynamic Neighbor Modeling for Review-Based Recommendation
inferred← citeshttps://doi.org/10.1007/s10489-021-02666-yopenalex-snapshot
A multi-task dual attention deep recommendation model using ratings and review helpfulness
inferred← citeshttps://doi.org/10.1007/s10489-022-03520-5openalex-snapshot
Leveraging mixed distribution of multi-head attention for sequential recommendation
inferred← citeshttps://doi.org/10.1007/s10489-023-04943-4openalex-snapshot
Improving rating predictions with time-varying attention and dual-optimizer
inferred← citeshttps://doi.org/10.1007/s10586-026-05949-6openalex-snapshot
A mixed deep neural network for addressing the cold-start problem in recommender systems
inferred← citeshttps://doi.org/10.1007/s11042-021-10529-4openalex-snapshot
Embedding metadata using deep collaborative filtering to address the cold start problem for the rating prediction task
inferred← citeshttps://doi.org/10.1007/s11063-023-11363-5openalex-snapshot
Influence of Review Properties in the Usefulness Analysis of Consumer Reviews: A Review-Based Recommender System for Rating Prediction
inferred← citeshttps://doi.org/10.1007/s11257-024-09416-yopenalex-snapshot
Deep shared learning and attentive domain mapping for cross-domain recommendation
inferred← citeshttps://doi.org/10.1007/s12652-021-03626-7openalex-snapshot
Integrating reviews and ratings into graph neural networks for rating prediction
inferred← citeshttps://doi.org/10.1007/s40747-024-01778-5openalex-snapshot
DMR: disentangled and denoised learning for multi-behavior recommendation
inferred← citeshttps://doi.org/10.1007/s44196-023-00288-5openalex-snapshot
A Hybrid Deep Learning Method to Extract Multi-features from Reviews and User–Item Relations for Rating Prediction
inferred← citeshttps://doi.org/10.1016/j.asoc.2021.107345openalex-snapshot
Unifying paragraph embeddings and neural collaborative filtering for hybrid recommendation
inferred← citeshttps://doi.org/10.1016/j.bdr.2025.100521openalex-snapshot
Deep attention dynamic representation learning networks for recommender system review modeling
inferred← citeshttps://doi.org/10.1016/j.ejor.2024.01.042openalex-snapshot
Review-based recommendation under preference uncertainty: An asymmetric deep learning framework
inferred← citeshttps://doi.org/10.1016/j.eswa.2021.114688openalex-snapshot
Joint aspect terms extraction and aspect categories detection via multi-task learning
inferred← citeshttps://doi.org/10.1016/j.eswa.2021.115752openalex-snapshot
Shared-view and specific-view information extraction for recommendation
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.116717openalex-snapshot
AENAR: An aspect-aware explainable neural attentional recommender model for rating predication
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.117317openalex-snapshot
Learning persona-driven personalized sentimental representation for review-based recommendation
inferred← citeshttps://doi.org/10.1016/j.eswa.2023.121120openalex-snapshot
Exploiting deep transformer models in textual review based recommender systems
inferred← citeshttps://doi.org/10.1016/j.im.2025.104267openalex-snapshot
The gap matters: An explainable customer dissatisfaction tracing analysis
inferred← citeshttps://doi.org/10.1016/j.ipm.2021.102715openalex-snapshot
Hierarchical temporal–spatial preference modeling for user consumption location prediction in Geo-Social Networks
inferred← citeshttps://doi.org/10.1016/j.ipm.2022.103166openalex-snapshot
Analyzing review sentiments and product images by parallel deep nets for personalized recommendation
inferred← citeshttps://doi.org/10.1016/j.knosys.2019.06.029openalex-snapshot
Multi-view factorization machines for mobile app recommendation based on hierarchical attention
inferred← citeshttps://doi.org/10.1016/j.knosys.2020.106664openalex-snapshot
Cross-domain recommendation with user personality
inferred← citeshttps://doi.org/10.1016/j.knosys.2020.106681openalex-snapshot
An adaptive deep learning method for item recommendation system
inferred← citeshttps://doi.org/10.1016/j.knosys.2021.107282openalex-snapshot
Learning product representations for generating reviews for cold products
inferred← citeshttps://doi.org/10.1016/j.knosys.2023.110438openalex-snapshot
Enhancing review-based user representation on learned social graph for recommendation
inferred← citeshttps://doi.org/10.1016/j.neunet.2022.10.001openalex-snapshot
Multi-Aspect enhanced Graph Neural Networks for recommendation
inferred← citeshttps://doi.org/10.1016/j.patrec.2021.02.007openalex-snapshot
Socially-driven multi-interaction attentive group representation learning for group recommendation
inferred← citeshttps://doi.org/10.1051/ro/2025151openalex-snapshot
Addressing the cold start problem in privacy preserving content-based recommender systems using hypercube graphs
inferred← citeshttps://doi.org/10.1080/1206212x.2026.2685822openalex-snapshot
A novel recommendation framework using sentiment and rating weighted association score framework
inferred← citeshttps://doi.org/10.1108/el-06-2020-0154openalex-snapshot
Using latent features for building an interpretable recommendation system
inferred← citeshttps://doi.org/10.1109/access.2019.2962075openalex-snapshot
A Review Semantics Based Model for Rating Prediction
inferred← citeshttps://doi.org/10.1109/access.2020.3013639openalex-snapshot
Aspect-Based Fashion Recommendation With Attention Mechanism
inferred← citeshttps://doi.org/10.1109/access.2020.3031621openalex-snapshot
Rating Prediction Based on Merge-CNN and Concise Attention Review Mining
inferred← citeshttps://doi.org/10.1109/access.2022.3217911openalex-snapshot
Neural Collaborative Filtering for Chinese Movies Based on Aspect-Aware Implicit Interactions
inferred← citeshttps://doi.org/10.1109/access.2023.3349291openalex-snapshot
An Attentive Aspect-Based Recommendation Model With Deep Neural Network
inferred← citeshttps://doi.org/10.1109/bigdata55660.2022.10020741openalex-snapshot
Multi-criteria Rating and Review based Recommendation Model
inferred← citeshttps://doi.org/10.1109/icdm50108.2020.00174openalex-snapshot
TADO: Time-Varying Attention with Dual-Optimizer Model
inferred← citeshttps://doi.org/10.1109/icist52614.2021.9440598openalex-snapshot
Mutual Attention Graph Neural Network Based on Joint Representation of Nodes and Reviews for Recommendation
inferred← citeshttps://doi.org/10.1109/icpeca60615.2024.10470983openalex-snapshot
A Focus on Female Consumer Review-Based Recommender Systems
inferred← citeshttps://doi.org/10.1109/isml60050.2024.11007400openalex-snapshot
A Review on Deep Learning Powered Online Product Recommender System in the Digital Market Place
inferred← citeshttps://doi.org/10.1109/tcss.2022.3181065openalex-snapshot
Recommendation Model Based on Enhanced Graph Convolution That Fuses Review Properties
inferred← citeshttps://doi.org/10.1109/tkde.2020.3010949openalex-snapshot
Adaptive Hierarchical Attention-Enhanced Gated Network Integrating Reviews for Item Recommendation
inferred← citeshttps://doi.org/10.1109/tkde.2023.3301884openalex-snapshot
Knowledge-Aware Collaborative Filtering With Pre-Trained Language Model for Personalized Review-Based Rating Prediction
inferred← citeshttps://doi.org/10.1109/tkde.2026.3699701openalex-snapshot
Reason4Rec: Deliberative User Preference Alignment of Large Language Models for Recommendation
inferred← citeshttps://doi.org/10.1109/tnnls.2022.3163789openalex-snapshot
Review Polarity-Wise Recommender
inferred← citeshttps://doi.org/10.1109/tnnls.2022.3171335openalex-snapshot
Modeling Self-Representation Label Correlations for Textual Aspects and Emojis Recommendation
inferred← citeshttps://doi.org/10.1109/tnsm.2022.3227188openalex-snapshot
Neural Attention Networks for Recommendation With Auxiliary Data
inferred← citeshttps://doi.org/10.1109/tsmc.2024.3522980openalex-snapshot
Correlation-Driven Explainable Recommendation With Aspect and Rating Boosted Representation Learning: A Unified Joint-Ranking Framework
inferred← citeshttps://doi.org/10.1109/wi-iat55865.2022.00030openalex-snapshot
Explainable Recommendation Enhancing Review Properties and PPLM
inferred← citeshttps://doi.org/10.1109/wi-iat59888.2023.00043openalex-snapshot
Aspect-Aware Multi-Criteria Recommendation Model with Aspect Representation Learning
inferred← citeshttps://doi.org/10.1111/exsy.70377openalex-snapshot
AEN ‐ GCL : Aspect‐Guided Embedding and Negative Sampling With Graph Contrastive Learning for Recommendation
inferred← citeshttps://doi.org/10.1142/s2196888823500124openalex-snapshot
An Item–Item Collaborative Filtering Recommender System Based on Item Reviews: An Approach with Deep Learning
inferred← citeshttps://doi.org/10.1145/3357154openalex-snapshot
Modeling Embedding Dimension Correlations via Convolutional Neural Collaborative Filtering
inferred← citeshttps://doi.org/10.1145/3372154openalex-snapshot
Local Variational Feature-Based Similarity Models for Recommending Top- N New Items
inferred← citeshttps://doi.org/10.1145/3382764openalex-snapshot
Exploiting Cross-session Information for Session-based Recommendation with Graph Neural Networks
inferred← citeshttps://doi.org/10.1145/3399630openalex-snapshot
A Weakly Supervised WordNet-Guided Deep Learning Approach to Extracting Aspect Terms from Online Reviews
inferred← citeshttps://doi.org/10.1145/3406109openalex-snapshot
Fine-Grained Privacy Detection with Graph-Regularized Hierarchical Attentive Representation Learning
inferred← citeshttps://doi.org/10.1145/3414841openalex-snapshot
Personalized Review Recommendation based on Users’ Aspect Sentiment
inferred← citeshttps://doi.org/10.1145/3432049openalex-snapshot
Multilingual Review-aware Deep Recommender System via Aspect-based Sentiment Analysis
inferred← citeshttps://doi.org/10.1145/3442381.3450038openalex-snapshot
Leveraging Review Properties for Effective Recommendation
inferred← citeshttps://doi.org/10.1145/3450353openalex-snapshot
Inductive Contextual Relation Learning for Personalization
inferred← citeshttps://doi.org/10.1145/3466640openalex-snapshot
Interpretable Aspect-Aware Capsule Network for Peer Review Based Citation Count Prediction
inferred← citeshttps://doi.org/10.1145/3471158.3472258openalex-snapshot
Understanding the Effectiveness of Reviews in E-commerce Top-N Recommendation
inferred← citeshttps://doi.org/10.1145/3483611openalex-snapshot
An Unsupervised Aspect-Aware Recommendation Model with Explanation Text Generation
inferred← citeshttps://doi.org/10.1145/3488560.3498508openalex-snapshot
Interpretable Relation Learning on Heterogeneous Graphs
inferred← citeshttps://doi.org/10.1145/3490477openalex-snapshot
Feature-Level Attentive ICF for Recommendation
inferred← citeshttps://doi.org/10.1145/3507782openalex-snapshot
Toward Personalized Answer Generation in E-Commerce via Multi-perspective Preference Modeling
inferred← citeshttps://doi.org/10.1145/3529954openalex-snapshot
Few-shot Aspect Category Sentiment Analysis via Meta-learning
inferred← citeshttps://doi.org/10.1145/3532188openalex-snapshot
Learning Aspect-Aware High-Order Representations from Ratings and Reviews for Recommendation
inferred← citeshttps://doi.org/10.1145/3532859openalex-snapshot
BanditProp: Bandit Selection of Review Properties for Effective Recommendation
inferred← citeshttps://doi.org/10.1145/3534678.3539130openalex-snapshot
Feature-aware Diversified Re-ranking with Disentangled Representations for Relevant Recommendation
inferred← citeshttps://doi.org/10.1145/3538703openalex-snapshot
Personalized Visualization Recommendation
inferred← citeshttps://doi.org/10.1145/3539618.3592053openalex-snapshot
Review-based Multi-intention Contrastive Learning for Recommendation
inferred← citeshttps://doi.org/10.1145/3565798openalex-snapshot
Dual Preference Distribution Learning for Item Recommendation
inferred← citeshttps://doi.org/10.1145/3570500openalex-snapshot
Modeling User Reviews through Bayesian Graph Attention Networks for Recommendation
inferred← citeshttps://doi.org/10.1145/3570509openalex-snapshot
Neural Topic Modeling via Discrete Variational Inference
inferred← citeshttps://doi.org/10.1145/3573385openalex-snapshot
Revisiting Graph-based Recommender Systems from the Perspective of Variational Auto-Encoder
inferred← citeshttps://doi.org/10.1145/3583780.3615012openalex-snapshot
printf: Preference Modeling Based on User Reviews with Item Images and Textual Information via Graph Learning
inferred← citeshttps://doi.org/10.1145/3617023.3617050openalex-snapshot
A Survey on Review - Aware Recommendation Systems
inferred← citeshttps://doi.org/10.1145/3625007.3627486openalex-snapshot
Utilizing Textual Reviews for Visualizing and Understanding User Preferences
inferred← citeshttps://doi.org/10.1145/3639479.3639501openalex-snapshot
Interpretable Recommendation Based on Review Aspect-Level Preferences
inferred← citeshttps://doi.org/10.1145/3663483openalex-snapshot
DIRECT: Dual Interpretable Recommendation with Multi-aspect Word Attribution
inferred← citeshttps://doi.org/10.1145/3701551.3703528openalex-snapshot
An Aspect Performance-aware Hypergraph Neural Network for Review-based Recommendation
inferred← citeshttps://doi.org/10.1145/3711856openalex-snapshot
Domain Counterfactual Data Augmentation for Explainable Recommendation
inferred← citeshttps://doi.org/10.1145/3742421openalex-snapshot
Review-based Recommender Systems: A Survey of Approaches, Challenges and Future Perspectives
inferred← citeshttps://doi.org/10.1145/3744661openalex-snapshot
Review-Aware Recommender Systems (RARSs): Recent Advances, Experimental Comparative Analysis, Discussions, and New Directions
inferred← citeshttps://doi.org/10.1145/3773966.3778013openalex-snapshot
HADSF: Aspect Aware Semantic Control for Explainable Recommendation
inferred← citeshttps://doi.org/10.1145/3804504.3804507openalex-snapshot
Sustainable Health-Aware Dining Recommendations Integrating Affective Insights, Contextual Signals, and Future Wearable Extensions
inferred← citeshttps://doi.org/10.1145/3843223openalex-snapshot
LLM-Driven Aspect-Based Semantic Alignment for Review-Based Recommendation
inferred← citeshttps://doi.org/10.18280/isi.280530openalex-snapshot
Leveraging Latent Dirichlet Allocation for Feature Extraction in User Comments: Enhancements to User-Centered Design in Indonesian Financial Technology
inferred← citeshttps://doi.org/10.18653/v1/2021.findings-emnlp.66openalex-snapshot
Recommend for a Reason: Unlocking the Power of Unsupervised Aspect-Sentiment Co-Extraction
inferred← citeshttps://doi.org/10.21203/rs.3.rs-2128324/v1openalex-snapshot
SARWAS Recommendation Framework Using Deep Learning
inferred← citeshttps://doi.org/10.2139/ssrn.6879761openalex-snapshot
A personalized recommendation model based on online reviews: an attribute-weighted random walk with restart approach
inferred← citeshttps://doi.org/10.31274/td-20240329-4openalex-snapshot
A deep learning odyssey on structured natural language processing
inferred← citeshttps://doi.org/10.3233/ida-230128openalex-snapshot
Asymmetric multilevel interactive attention network integrating reviews for item recommendation
inferred← citeshttps://doi.org/10.32657/10356/155781openalex-snapshot
Exploiting side information for effective recommendation
inferred← citeshttps://doi.org/10.3390/app112411890openalex-snapshot
Enhancing Recommender System with Collaborative Filtering and User Experiences Filtering
inferred← citeshttps://doi.org/10.3390/app13031241openalex-snapshot
Dual-Track Lifelong Machine Learning-Based Fine-Grained Product Quality Analysis
inferred← citeshttps://doi.org/10.3390/electronics13142811openalex-snapshot
Explicitly Exploiting Implicit User and Item Relations in Graph Convolutional Network (GCN) for Recommendation
inferred← citeshttps://doi.org/10.3390/electronics14010033openalex-snapshot
NRDPA: Review-Aware Neural Recommendation with Dynamic Personalized Attention
inferred← citeshttps://doi.org/10.3390/electronics14040811openalex-snapshot
Connecting Visual Data to Privacy: Predicting and Measuring Privacy Risks in Images
inferred← citeshttps://doi.org/10.48550/arxiv.2005.09344openalex-snapshot
Try This Instead: Personalized and Interpretable Substitute Recommendation
inferred← citeshttps://doi.org/10.48550/arxiv.2107.03226openalex-snapshot
Graphing else matters: exploiting aspect opinions and ratings in explainable graph-based recommendations
inferred← citeshttps://doi.org/10.48550/arxiv.2107.03385openalex-snapshot
Rating and aspect-based opinion graph embeddings for explainable recommendations
inferred← citeshttps://doi.org/10.9728/dcs.2020.21.9.1575openalex-snapshot
A Study on the Personalization Recommendation Service Incorporating Review-based Customer Profile
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.