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BS-SC: An Unsupervised Approach for Detecting Shilling Profiles in Collaborative Recommender Systems
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/sec.1389openalex-snapshot
An ensemble method for detecting shilling attacks based on ordered item sequences
inferredcites →https://doi.org/10.1007/978-1-4899-7637-6openalex-snapshot
Recommender Systems Handbook
inferredcites →https://doi.org/10.1007/978-3-319-59288-6_34openalex-snapshot
Abnormal Group User Detection in Recommender Systems Using Multi-dimension Time Series
inferredcites →https://doi.org/10.1007/978-3-642-37401-2_36openalex-snapshot
A Probabilistic Model for Diversifying Recommendation Lists
inferredcites →https://doi.org/10.1007/s11257-008-9050-4openalex-snapshot
Unsupervised strategies for shilling detection and robust collaborative filtering
inferredcites →https://doi.org/10.1007/s11280-012-0164-6openalex-snapshot
Shilling attack detection utilizing semi-supervised learning method for collaborative recommender system
inferredcites →https://doi.org/10.1016/j.ins.2015.02.019openalex-snapshot
A novel item anomaly detection approach against shilling attacks in collaborative recommendation systems using the dynamic time interval segmentation technique
inferredcites →https://doi.org/10.1016/j.knosys.2014.04.020openalex-snapshot
HHT–SVM: An online method for detecting profile injection attacks in collaborative recommender systems
inferredcites →https://doi.org/10.1016/j.knosys.2016.02.008openalex-snapshot
Re-scale AdaBoost for attack detection in collaborative filtering recommender systems
inferredcites →https://doi.org/10.1016/j.knosys.2016.08.011openalex-snapshot
Estimating user behavior toward detecting anomalous ratings in rating systems
inferredcites →https://doi.org/10.1016/j.neucom.2015.12.137openalex-snapshot
SVM-TIA a shilling attack detection method based on SVM and target item analysis in recommender systems
inferredcites →https://doi.org/10.1016/j.neucom.2017.02.052openalex-snapshot
Spotting anomalous ratings for rating systems by analyzing target users and items
inferredcites →https://doi.org/10.1049/iet-ifs.2015.0067openalex-snapshot
Supervised approach for detecting average over popular items attack in collaborative recommender systems
inferredcites →https://doi.org/10.1109/icassp.2014.6854162openalex-snapshot
Spectral clustering with imbalanced data
inferredcites →https://doi.org/10.1109/mis.2016.37openalex-snapshot
Uncovering and Predicting Human Behaviors
inferredcites →https://doi.org/10.1109/mlsp.2013.6661953openalex-snapshot
Graph-based detection of shilling attacks in recommender systems
inferredcites →https://doi.org/10.1109/socpar.2011.6089138openalex-snapshot
Detection of shilling attacks in collaborative filtering recommender systems
inferredcites →https://doi.org/10.1145/1060745.1060754openalex-snapshot
Improving recommendation lists through topic diversification
inferredcites →https://doi.org/10.1145/1097047.1097061openalex-snapshot
Preventing shilling attacks in online recommender systems
inferredcites →https://doi.org/10.1145/1150402.1150508openalex-snapshot
Attack detection in time series for recommender systems
inferredcites →https://doi.org/10.1145/1390156.1390300openalex-snapshot
Graph transduction via alternating minimization
inferredcites →https://doi.org/10.1145/2348283.2348297openalex-snapshot
Explicit relevance models in intent-oriented information retrieval diversification
inferredcites →https://doi.org/10.1145/2505515.2505700openalex-snapshot
Uncovering collusive spammers in Chinese review websites
inferredcites →https://doi.org/10.1145/2505515.2507875openalex-snapshot
A belief propagation approach for detecting shilling attacks in collaborative filtering
inferredcites →https://doi.org/10.1145/2566486.2568008openalex-snapshot
Robust multivariate autoregression for anomaly detection in dynamic product ratings
inferredcites →https://doi.org/10.1145/2645710.2645722openalex-snapshot
Attacking item-based recommender systems with power items
inferredcites →https://doi.org/10.1145/988672.988726openalex-snapshot
Shilling recommender systems for fun and profit
inferredcites →https://doi.org/10.1155/2015/490261openalex-snapshot
Abnormal Profiles Detection Based on Time Series and Target Item Analysis for Recommender Systems
inferredcites →https://doi.org/10.1209/0295-5075/100/48004openalex-snapshot
Scaling behavior of online human activity
inferredcites →https://doi.org/10.1287/ijoc.1100.0440openalex-snapshot
Shilling Attack Detection—A New Approach for a Trustworthy Recommender System
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4463658openalex-extracted
Credrec: A Unified Framework for Handling Shilling Attacks and Generating Credible Recommendations
inferred← citeshttps://doi.org/10.1007/s11276-023-03301-zopenalex-snapshot
Applying machine learning enabled myriad fragment empirical modes in 5G communications to detect profile injection attacks
inferred← citeshttps://doi.org/10.1016/j.cose.2023.103407openalex-snapshot
Detecting malicious reviews and users affecting social reviewing systems: A survey
inferred← citeshttps://doi.org/10.1016/j.cose.2024.104030openalex-snapshot
A recommendation attack detection approach integrating CNN with Bagging
inferred← citeshttps://doi.org/10.1016/j.ipm.2022.103031openalex-snapshot
Detecting shilling groups in online recommender systems based on graph convolutional network
inferred← citeshttps://doi.org/10.1016/j.ipm.2026.105178openalex-snapshot
Target item identification for injection attacks in recommender systems via graph-enhanced user representations
inferred← citeshttps://doi.org/10.1016/j.knosys.2023.110931openalex-snapshot
Recommendation attack detection based on improved Meta Pseudo Labels
inferred← citeshttps://doi.org/10.1109/icaica52286.2021.9497958openalex-snapshot
Group attack detection in recommender systems based on triangle dense subgraph mining
inferred← citeshttps://doi.org/10.1109/icatme50232.2021.9732722openalex-snapshot
Review of Various types of Spam and Spammer Detection Techniques
inferred← citeshttps://doi.org/10.1109/tkde.2021.3128365openalex-snapshot
2021 Index IEEE Transactions on Knowledge and Data Engineering Vol. 33
inferred← citeshttps://doi.org/10.1109/tkde.2021.3132953openalex-snapshot
A Deep Dual Adversarial Network for Cross-Domain Recommendation
inferred← citeshttps://doi.org/10.1109/tkde.2024.3485880openalex-snapshot
Handling Low Homophily in Recommender Systems With Partitioned Graph Transformer
inferred← citeshttps://doi.org/10.1109/tkde.2025.3565793openalex-snapshot
Camouflaged Variational Graph AutoEncoder against Attribute Inference Attacks for Cross-Domain Recommendation
inferred← citeshttps://doi.org/10.1109/tkde.2026.3722474openalex-snapshot
Efficient Poisoning Attacks Against Reinforcement Learning-Based Recommender Systems
inferred← citeshttps://doi.org/10.1145/3677328openalex-snapshot
Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures
inferred← citeshttps://doi.org/10.1155/2022/2323132openalex-snapshot
A Shilling Group Detection Framework Based on Deep Learning Techniques
inferred← citeshttps://doi.org/10.1155/2022/5807690openalex-snapshot
[Retracted] Big Data Analytics Model for Distributed Document Using Hybrid Optimization with K‐Means Clustering
inferred← citeshttps://doi.org/10.2174/0123520965265325231206094044openalex-snapshot
Enhancing Recommendation Systems with Skew Deviation Bias for Shilling Attack Detection
inferred← citeshttps://doi.org/10.3390/app121910135openalex-snapshot
Improving Deep Learning-Based Recommendation Attack Detection Using Harris Hawks Optimization
inferred← citeshttps://doi.org/10.4108/eai.2-11-2021.171754openalex-snapshot
Hybrid CNN and RNN-based shilling attack framework in social recommender networks
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