Unsupervised and supervised methods for the detection of hurriedly created profiles in recommender systems
暂无分享,去创建一个
Paraskevi Fragopoulou | Harris Papadakis | Costas Panagiotakis | C. Panagiotakis | P. Fragopoulou | H. Papadakis
[1] Paraskevi Fragopoulou,et al. SCoR: A Synthetic Coordinate based Recommender system , 2017, Expert Syst. Appl..
[2] Peng Zhang,et al. UD-HMM: An unsupervised method for shilling attack detection based on hidden Markov model and hierarchical clustering , 2018, Knowl. Based Syst..
[3] Guy Shani,et al. A Survey of Accuracy Evaluation Metrics of Recommendation Tasks , 2009, J. Mach. Learn. Res..
[4] Wei-Ho Tsai,et al. Improving search engine optimization (SEO) by using hybrid modified MCDM models , 2018, Artificial Intelligence Review.
[5] Gediminas Adomavicius,et al. Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.
[6] Georgios Tziritas,et al. MRF-based segmentation and unsupervised classification for building and road detection in peri-urban areas of high-resolution satellite images , 2016 .
[7] Zhongmin Cai,et al. Estimating user behavior toward detecting anomalous ratings in rating systems , 2016, Knowl. Based Syst..
[8] Fuzhi Zhang,et al. HHT-SVM: An online method for detecting profile injection attacks in collaborative recommender systems , 2014, Knowl. Based Syst..
[9] Fan Yang,et al. Detection of Shilling Attack Based on Bayesian Model and User Embedding , 2018, 2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI).
[10] Gediminas Adomavicius,et al. Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques , 2012, IEEE Transactions on Knowledge and Data Engineering.
[11] John Riedl,et al. An Algorithmic Framework for Performing Collaborative Filtering , 1999, SIGIR Forum.
[12] Beibei Zhang,et al. Uncovering anomalous rating behaviors for rating systems , 2018, Neurocomputing.
[13] Bamshad Mobasher,et al. Classification features for attack detection in collaborative recommender systems , 2006, KDD '06.
[14] Ahmet Murat Turk,et al. Robustness analysis of multi-criteria collaborative filtering algorithms against shilling attacks , 2019, Expert Syst. Appl..
[15] Qingshan Li,et al. Shilling attacks against collaborative recommender systems: a review , 2018, Artificial Intelligence Review.
[16] Heri Ramampiaro,et al. Securing Tag-based recommender systems against profile injection attacks: A comparative study , 2018, ArXiv.
[17] Bamshad Mobasher,et al. Model-Based Collaborative Filtering as a Defense against Profile Injection Attacks , 2006, AAAI.
[18] Zongben Xu,et al. Re-scale AdaBoost for attack detection in collaborative filtering recommender systems , 2015, Knowl. Based Syst..
[19] Yanchun Zhang,et al. Shilling attack detection utilizing semi-supervised learning method for collaborative recommender system , 2013, World Wide Web.
[20] Michael R. Lyu,et al. Mining Web Graphs for Recommendations , 2012, IEEE Transactions on Knowledge and Data Engineering.
[21] F. Maxwell Harper,et al. The MovieLens Datasets: History and Context , 2016, TIIS.
[22] Derry O'Sullivan,et al. Improving Case-Based Recommendation: A Collaborative Filtering Approach , 2002, ECCBR.
[23] Patrick P. K. Chan,et al. Shilling attack based on item popularity and rated item correlation against collaborative filtering , 2019, Int. J. Mach. Learn. Cybern..
[24] Neil J. Hurley,et al. Robust Collaborative Recommendation , 2011, Recommender Systems Handbook.
[25] Lior Rokach,et al. Recommender Systems: Introduction and Challenges , 2015, Recommender Systems Handbook.
[26] Costas Panagiotakis. Point Clustering via Voting Maximization , 2015, J. Classif..
[27] Geoffrey E. Hinton,et al. Restricted Boltzmann machines for collaborative filtering , 2007, ICML '07.
[28] Mainak Chatterjee,et al. Detection of profile injection attacks in social recommender systems using outlier analysis , 2017, 2017 IEEE International Conference on Big Data (Big Data).
[29] Genevieve Gorrell,et al. Generalized Hebbian Algorithm for Incremental Singular Value Decomposition in Natural Language Processing , 2006, EACL.
[30] Paraskevi Fragopoulou,et al. Detection of Hurriedly Created Abnormal Profiles in Recommender Systems , 2018, 2018 International Conference on Intelligent Systems (IS).
[31] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[32] Martin Ester,et al. A matrix factorization technique with trust propagation for recommendation in social networks , 2010, RecSys '10.
[33] Paraskevi Fragopoulou,et al. Distributed detection of communities in complex networks using synthetic coordinates , 2014 .
[34] Junhao Wen,et al. SVM-TIA a shilling attack detection method based on SVM and target item analysis in recommender systems , 2016, Neurocomputing.
[35] Xiaoyu Du,et al. Outer Product-based Neural Collaborative Filtering , 2018, IJCAI.
[36] Bamshad Mobasher,et al. Defending recommender systems: detection of profile injection attacks , 2007, Service Oriented Computing and Applications.
[37] Mariana Belgiu,et al. Random forest in remote sensing: A review of applications and future directions , 2016 .
[38] Wolfgang Nejdl,et al. Preventing shilling attacks in online recommender systems , 2005, WIDM '05.
[39] Luís Macedo,et al. Emotion-Based Recommender System for Overcoming the Problem of Information Overload , 2013, PAAMS.
[40] HongYun Cai,et al. An Unsupervised Method for Detecting Shilling Attacks in Recommender Systems by Mining Item Relationship and Identifying Target Items , 2019, Comput. J..
[41] Greg Linden,et al. Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .
[42] Jae Kyeong Kim,et al. A literature review and classification of recommender systems research , 2012, Expert Syst. Appl..
[43] Nikos Komodakis,et al. Interactive image segmentation based on synthetic graph coordinates , 2013, Pattern Recognit..