A dual hybrid recommender system based on SCoR and the random forest

[1]  Zhang Xiong,et al.  Item Category Aware Conditional Restricted Boltzmann Machine Based Recommendation , 2015, ICONIP.

[2]  Yi Fang,et al.  Neural Citation Network for Context-Aware Citation Recommendation , 2017, SIGIR.

[3]  Mojtaba Salehi,et al.  Hybrid recommendation approach for learning material based on sequential pattern of the accessed material and the learner's preference tree , 2013, Knowl. Based Syst..

[4]  Xuanjing Huang,et al.  Hashtag Recommendation for Multimodal Microblog Using Co-Attention Network , 2017, IJCAI.

[5]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[6]  Xiaoyu Du,et al.  Outer Product-based Neural Collaborative Filtering , 2018, IJCAI.

[7]  Michael S. Lew,et al.  Deep learning for visual understanding: A review , 2016, Neurocomputing.

[8]  Genevieve Gorrell,et al.  Generalized Hebbian Algorithm for Incremental Singular Value Decomposition in Natural Language Processing , 2006, EACL.

[9]  Paraskevi Fragopoulou,et al.  Distributed detection of communities in complex networks using synthetic coordinates , 2014 .

[10]  R. Logesh,et al.  Exploring Hybrid Recommender Systems for Personalized Travel Applications , 2018, Cognitive Informatics and Soft Computing.

[11]  Robert Tappan Morris,et al.  Vivaldi: a decentralized network coordinate system , 2004, SIGCOMM '04.

[12]  Gediminas Adomavicius,et al.  Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques , 2012, IEEE Transactions on Knowledge and Data Engineering.

[13]  Nikos Komodakis,et al.  Interactive image segmentation based on synthetic graph coordinates , 2013, Pattern Recognit..

[14]  Fan Min,et al.  Three-way recommender systems based on random forests , 2016, Knowl. Based Syst..

[15]  Yehuda Koren,et al.  Matrix Factorization Techniques for Recommender Systems , 2009, Computer.

[16]  Nikolaos Doulamis,et al.  Deep Learning for Computer Vision: A Brief Review , 2018, Comput. Intell. Neurosci..

[17]  F. Maxwell Harper,et al.  The MovieLens Datasets: History and Context , 2016, TIIS.

[18]  Philip S. Thomas,et al.  Personalized Ad Recommendation Systems for Life-Time Value Optimization with Guarantees , 2015, IJCAI.

[19]  Jonathan L. Herlocker,et al.  Evaluating collaborative filtering recommender systems , 2004, TOIS.

[20]  Paraskevi Fragopoulou,et al.  Detection of Hurriedly Created Abnormal Profiles in Recommender Systems , 2018, 2018 International Conference on Intelligent Systems (IS).

[21]  Bamshad Mobasher,et al.  Model-Based Collaborative Filtering as a Defense against Profile Injection Attacks , 2006, AAAI.

[22]  Sang-Wook Kim,et al.  Data imputation using a trust network for recommendation via matrix factorization , 2018, Comput. Sci. Inf. Syst..

[23]  Gilles Louppe,et al.  Understanding Random Forests: From Theory to Practice , 2014, 1407.7502.

[24]  Paraskevi Fragopoulou,et al.  Unsupervised and supervised methods for the detection of hurriedly created profiles in recommender systems , 2020, International Journal of Machine Learning and Cybernetics.

[25]  Zhang Xiong,et al.  User Occupation Aware Conditional Restricted Boltzmann Machine Based Recommendation , 2016, 2016 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData).

[26]  Paraskevi Fragopoulou,et al.  Personalized Video Summarization Based Exclusively on User Preferences , 2020, ECIR.

[27]  Juan-Zi Li,et al.  Typicality-Based Collaborative Filtering Recommendation , 2014, IEEE Transactions on Knowledge and Data Engineering.

[28]  Dilruk Perera,et al.  LSTM Networks for Online Cross-Network Recommendations , 2018, IJCAI.

[29]  Sarika Jain,et al.  Trends, problems and solutions of recommender system , 2015, International Conference on Computing, Communication & Automation.