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2020 – today
- 2024
[j25]Olanrewaju Sanda, Michalis Pavlidis
, Nikolaos Polatidis:
A deep learning approach for host-based cryptojacking malware detection. Evol. Syst. 15(1): 41-56 (2024)- [j24]Benedict Ngaibe Mbungang, Joan Beri Ali Wacka, Franklin Tchakounté, Nikolaos Polatidis, Jean Michel Nlong II, Daniel Tieudjo:
Detecting Android Malware with Convolutional Neural Networks and Hilbert Space-Filling Curves. SN Comput. Sci. 5(7): 810 (2024) - [j23]Nikolaos Polatidis, Stelios Kapetanakis, Marcello Trovati, Ioannis Korkontzelos, Yannis Manolopoulos:
FSSDroid: Feature subset selection for Android malware detection. World Wide Web (WWW) 27(5): 50 (2024) - 2023
- [j22]Marcello Trovati, Khalid Teli, Nikolaos Polatidis, Ufuk Alpsahin Cullen, Simon Bolton:
Artificial Intuition for Automated Decision-Making. Appl. Artif. Intell. 37(1) (2023) - [j21]Olanrewaju Sanda, Michalis Pavlidis, Saeed Seraj, Nikolaos Polatidis:
Long-Range attack detection on permissionless blockchains using Deep Learning. Expert Syst. Appl. 218: 119606 (2023) - [j20]Saeed Seraj, Siavash Khodambashi, Michalis Pavlidis, Nikolaos Polatidis:
MVDroid: an android malicious VPN detector using neural networks. Neural Comput. Appl. 35(29): 21555-21565 (2023) - [c26]Saeed Seraj, Elias Pimenidis, Michalis Pavlidis, Stelios Kapetanakis, Marcello Trovati, Nikolaos Polatidis:
BotDroid: Permission-Based Android Botnet Detection Using Neural Networks. EANN 2023: 71-84 - [c25]Nikolaos Polatidis, Elias Pimenidis, Marcello Trovati, Lazaros Iliadis:
VPNDroid: Malicious Android VPN Detection Using a CNN-RF Method. ICANN (10) 2023: 444-453 - 2022
- [j19]Olanrewaju Sanda, Michalis Pavlidis, Nikolaos Polatidis:
A Regulatory Readiness Assessment Framework for Blockchain Adoption in Healthcare. Digit. 2(1): 65-87 (2022) - [j18]Saeed Seraj, Siavash Khodambashi, Michalis Pavlidis, Nikolaos Polatidis:
HamDroid: permission-based harmful android anti-malware detection using neural networks. Neural Comput. Appl. 34(18): 15165-15174 (2022) - [c24]Nikolaos Polatidis, Stelios Kapetanakis, Elias Pimenidis, Yannis Manolopoulos:
Fast and Accurate Evaluation of Collaborative Filtering Recommendation Algorithms. ACIIDS (1) 2022: 623-634 - [c23]Saeed Seraj, Michalis Pavlidis, Nikolaos Polatidis:
TrojanDroid: Android Malware Detection for Trojan Discovery Using Convolutional Neural Networks. EANN 2022: 203-212 - [c22]Marcello Trovati, Olayinka Johnny, Xiaolong Xu, Nikolaos Polatidis:
A New Model for Artificial Intuition. ICANN (1) 2022: 454-465 - [c21]Amol Dhaliwal, Nikolaos Polatidis, Elias Pimenidis:
A Novel LSTM-CNN Architecture to Forecast Stock Prices. ICANN (1) 2022: 466-477 - 2021
- [c20]Nikolaos Polatidis, Stelios Kapetanakis, Elias Pimenidis:
Recommender Systems Algorithm Selection Using Machine Learning. EANN 2021: 477-487 - [c19]Eleftherios Bandis, Nikolaos Polatidis, Maria Diapouli, Stelios Kapetanakis:
Data Stream Harmonization For Heterogeneous Workflows. ECMS 2021: 42-47 - 2020
- [j17]Nikolaos Polatidis, Elias Pimenidis, Michalis Pavlidis, Spyridon Papastergiou, Haralambos Mouratidis:
From product recommendation to cyber-attack prediction: generating attack graphs and predicting future attacks. Evol. Syst. 11(3): 479-490 (2020) - [j16]Merton Lansley, Francois Mouton, Stelios Kapetanakis, Nikolaos Polatidis:
SEADer++: social engineering attack detection in online environments using machine learning. J. Inf. Telecommun. 4(3): 346-362 (2020) - [j15]Nikolaos Polatidis, Antonios Papaleonidas, Elias Pimenidis, Lazaros Iliadis:
An explanation-based approach for experiment reproducibility in recommender systems. Neural Comput. Appl. 32(16): 12259-12266 (2020) - [j14]Stelios Kapetanakis, Nikolaos Polatidis, Gharbi Alshammari, Miltos Petridis:
A novel recommendation method based on general matrix factorization and artificial neural networks. Neural Comput. Appl. 32(16): 12327-12334 (2020) - [c18]Kareem Amin, Stelios Kapetanakis, Nikolaos Polatidis, Klaus-Dieter Althoff, Andreas Dengel:
DeepKAF: A Heterogeneous CBR & Deep Learning Approach for NLP Prototyping. INISTA 2020: 1-7 - [c17]Merton Lansley, Stelios Kapetanakis, Nikolaos Polatidis:
SEADer++ v2: Detecting Social Engineering Attacks using Natural Language Processing and Machine Learning. INISTA 2020: 1-6 - [c16]Saeed Seraj, Michalis Pavlidis, Nikolaos Polatidis:
A Novel Dataset for Fake Android Anti-Malware Detection. WIMS 2020: 205-209
2010 – 2019
- 2019
- [j13]Nikolaos Polatidis, Elias Pimenidis, Andrew Fish, Stelios Kapetanakis:
A Guideline-Based Approach for Assisting with the Reproducibility of Experiments in Recommender Systems Evaluation. Int. J. Artif. Intell. Tools 28(8): 1960011:1-1960011:16 (2019) - [j12]Gharbi Alshammari, Jose L. Jorro-Aragoneses, Nikolaos Polatidis, Stelios Kapetanakis, Elias Pimenidis, Miltos Petridis:
A switching multi-level method for the long tail recommendation problem. J. Intell. Fuzzy Syst. 37(6): 7189-7198 (2019) - [j11]Elias Pimenidis, Nikolaos Polatidis, Haralambos Mouratidis:
Mobile recommender systems: Identifying the major concepts. J. Inf. Sci. 45(3) (2019) - [j10]Gharbi Alshammari, Stelios Kapetanakis, Abdullah Alshammari, Nikolaos Polatidis, Miltos Petridis:
Improved Movie Recommendations Based on a Hybrid Feature Combination Method. Vietnam. J. Comput. Sci. 6(3): 363-376 (2019) - [c15]Merton Lansley, Nikolaos Polatidis, Stelios Kapetanakis, Kareem Amin, George Samakovitis, Miltos Petridis:
Seen the villains: Detecting Social Engineering Attacks using Case-based Reasoning and Deep Learning. ICCBR Workshops 2019: 39-48 - [c14]Abdullah Alshammari, Stelios Kapetanakis, Nikolaos Polatidis, Roger Evans, Gharbi Alshammari:
Twitter User Modeling Based on Indirect Explicit Relationships for Personalized Recommendations. ICCCI (1) 2019: 93-105 - [c13]Merton Lansley, Nikolaos Polatidis, Stelios Kapetanakis:
SEADer: A Social Engineering Attack Detection Method Based on Natural Language Processing and Artificial Neural Networks. ICCCI (1) 2019: 686-696 - [c12]Elias Pimenidis, Nikolaos Polatidis:
Secure Social Media Spaces for Communities of Vulnerable People. ICGS3 2019 - [c11]Gharbi Alshammari, Jose L. Jorro-Aragoneses, Stelios Kapetanakis, Nikolaos Polatidis, Miltos Petridis:
A Switching Approach that Improves Prediction Accuracy for Long Tail Recommendations. IntelliSys (1) 2019: 18-28 - [c10]Kareem Amin, Stelios Kapetanakis, Nikolaos Polatidis, Klaus-Dieter Althoff, Andreas Dengel, Miltos Petridis:
Building Knowledge Intensive Architectures for Heterogeneous NLP Workflows. SGAI Conf. 2019: 152-157 - 2018
- [j9]Nikolaos Polatidis, Michalis Pavlidis, Haralambos Mouratidis:
Cyber-attack path discovery in a dynamic supply chain maritime risk management system. Comput. Stand. Interfaces 56: 74-82 (2018) - [c9]Gharbi Alshammari, Stelios Kapetanakis, Nikolaos Polatidis, Miltos Petridis:
A Triangle Multi-level Item-Based Collaborative Filtering Method that Improves Recommendations. EANN 2018: 145-157 - [c8]Nikolaos Polatidis, Elias Pimenidis:
Reproduction of Experiments in Recommender Systems Evaluation Based on Explanations. EANN 2018: 194-200 - [c7]Abdullah Alshammari, Stelios Kapetanakis, Roger Evans, Nikolaos Polatidis, Gharbi Alshammari:
User Modeling on Twitter with Exploiting Explicit Relationships for Personalized Recommendations. HIS 2018: 135-145 - [c6]Gharbi Alshammari, Stelios Kapetanakis, Abdullah Alshammari, Nikolaos Polatidis, Miltos Petridis:
A Hybrid Feature Combination Method that Improves Recommendations. ICCCI (1) 2018: 209-218 - [c5]Nikolaos Polatidis, Stelios Kapetanakis, Elias Pimenidis, Konstantinos Kosmidis:
Reproducibility of Experiments in Recommender Systems Evaluation. AIAI 2018: 401-409 - [i8]Nikolaos Polatidis, Christos K. Georgiadis:
A multi-level collaborative filtering method that improves recommendations. CoRR abs/1804.08891 (2018) - [i7]Nikolaos Polatidis, Elias Pimenidis, Michalis Pavlidis, Spyridon Papastergiou, Haralambos Mouratidis:
From product recommendation to cyber-attack prediction: Generating attack graphs and predicting future attacks. CoRR abs/1804.10276 (2018) - [i6]Elias Pimenidis, Nikolaos Polatidis, Haralambos Mouratidis:
Mobile recommender systems: Identifying the major concepts. CoRR abs/1805.02276 (2018) - 2017
- [b1]Nikolaos Polatidis:
Recommendations in mobile commerce environments: supporting quality and privacy requirements. University of Macedonia, Greece, 2017 - [j8]Nikolaos Polatidis, Christos K. Georgiadis:
A dynamic multi-level collaborative filtering method for improved recommendations. Comput. Stand. Interfaces 51: 14-21 (2017) - [j7]Nikolaos Polatidis, Christos K. Georgiadis, Elias Pimenidis, Haralambos Mouratidis:
Privacy-preserving collaborative recommendations based on random perturbations. Expert Syst. Appl. 71: 18-25 (2017) - [j6]Nikolaos Polatidis, Christos K. Georgiadis, Elias Pimenidis, Emmanouil Stiakakis:
Privacy-preserving recommendations in context-aware mobile environments. Inf. Comput. Secur. 25(1): 62-79 (2017) - [j5]Christos K. Georgiadis, Nikolaos Polatidis, Haralambos Mouratidis, Elias Pimenidis:
A Method for Privacy-preserving Collaborative Filtering Recommendations. J. Univers. Comput. Sci. 23(2): 146-166 (2017) - [c4]Nikolaos Polatidis, Elias Pimenidis, Michalis Pavlidis, Haralambos Mouratidis:
Recommender Systems Meeting Security: From Product Recommendation to Cyber-Attack Prediction. EANN 2017: 508-519 - [i5]Nikolaos Polatidis, Christos K. Georgiadis:
A dynamic multi-level collaborative filtering method for improved recommendations. CoRR abs/1702.01713 (2017) - 2016
- [j4]Nikolaos Polatidis, Christos K. Georgiadis:
A multi-level collaborative filtering method that improves recommendations. Expert Syst. Appl. 48: 100-110 (2016) - 2015
- [j3]Nikolaos Polatidis, Christos K. Georgiadis:
A ubiquitous recommender system based on collaborative filtering and social networking data. Int. J. Intell. Eng. Informatics 3(2/3): 186-204 (2015) - [c3]Nikolaos Polatidis, Christos K. Georgiadis, Elias Pimenidis, Emmanouil Stiakakis:
A Method for Privacy-Preserving Context-Aware Mobile Recommendations. e-Democracy 2015: 62-74 - 2014
- [c2]Nikolaos Polatidis, Christos K. Georgiadis:
Factors Influencing the Quality of the User Experience in Ubiquitous Recommender Systems. HCI (21) 2014: 369-379 - [i4]Nikolaos Polatidis:
SFA Referee Allocation Scheme. CoRR abs/1408.6661 (2014) - [i3]Nikolaos Polatidis:
Chatbot for admissions. CoRR abs/1408.6762 (2014) - [i2]Nikolaos Polatidis, Christos K. Georgiadis:
Factors Influencing the Quality of the User Experience in Ubiquitous Recommender Systems. CoRR abs/1408.6926 (2014) - [i1]Nikolaos Polatidis, Christos K. Georgiadis:
Mobile recommender systems: An overview of technologies and challenges. CoRR abs/1408.6930 (2014) - 2013
- [j2]Peter J. Hancox, Nikolaos Polatidis:
An evaluation of keyword, string similarity and very shallow syntactic matching for a university admissions processing infobot. Comput. Sci. Inf. Syst. 10(4): 1703-1726 (2013) - [j1]Nikolaos Polatidis, Christos K. Georgiadis:
Recommender Systems: The Importance of Personalization in E-Business Environments. Int. J. E Entrepreneurship Innov. 4(4): 32-46 (2013) - 2012
- [c1]Peter J. Hancox, Nikolaos Polatidis:
Query Matching Evaluation in an Infobot for University Admissions Processing. SLATE 2012: 149-161
Coauthor Index
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last updated on 2024-11-07 20:30 CET by the dblp team
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