Nikolaos Polatidis

发表

A Regulatory Readiness Assessment Framework for Blockchain Adoption in Healthcare

Olanrewaju Sanda, Michalis Pavlidis, Nikolaos Polatidis, 2022, Digit..

HamDroid: permission-based harmful android anti-malware detection using neural networks

Michalis Pavlidis, Nikolaos Polatidis, S. Khodambashi, 2022, Neural Computing and Applications.

Mobile recommender systems: Identifying the major concepts

Haralambos Mouratidis, Nikolaos Polatidis, Elias Pimenidis, 2018, J. Inf. Sci..

Privacy-preserving recommendations in context-aware mobile environments

Nikolaos Polatidis, Elias Pimenidis, Christos K. Georgiadis, 2017, Inf. Comput. Secur..

A Method for Privacy-Preserving Context-Aware Mobile Recommendations

Nikolaos Polatidis, Elias Pimenidis, Christos K. Georgiadis, 2015, e-Democracy.

A ubiquitous recommender system based on collaborative filtering and social networking data

Nikolaos Polatidis, Christos K. Georgiadis, C. Georgiadis, 2015, Int. J. Intell. Eng. Informatics.

Factors Influencing the Quality of the User Experience in Ubiquitous Recommender Systems

Nikolaos Polatidis, Christos K. Georgiadis, C. Georgiadis, 2014, HCI.

From product recommendation to cyber-attack prediction: generating attack graphs and predicting future attacks

Haralambos Mouratidis, Nikolaos Polatidis, Elias Pimenidis, 2018, Evol. Syst..

A novel recommendation method based on general matrix factorization and artificial neural networks

Miltos Petridis, Gharbi Alshammari, Nikolaos Polatidis, 2019, Neural Computing and Applications.

Improved Movie Recommendations Based on a Hybrid Feature Combination Method

Miltos Petridis, Gharbi Alshammari, Nikolaos Polatidis, 2019, Vietnam. J. Comput. Sci..

A Hybrid Feature Combination Method that Improves Recommendations

Miltos Petridis, Gharbi Alshammari, Nikolaos Polatidis, 2018, ICCCI.

A Triangle Multi-level Item-Based Collaborative Filtering Method that Improves Recommendations

Miltos Petridis, Gharbi Alshammari, Nikolaos Polatidis, 2018, EANN.

A dynamic multi-level collaborative filtering method for improved recommendations

Nikolaos Polatidis, Christos K. Georgiadis, C. Georgiadis, 2017, Comput. Stand. Interfaces.

A multi-level collaborative filtering method that improves recommendations pdf

Nikolaos Polatidis, Christos K. Georgiadis, C. Georgiadis, 2016, Expert Syst. Appl..

Recommender Systems Algorithm Selection Using Machine Learning

Nikolaos Polatidis, Stelios Kapetanakis, Elias Pimenidis, 2021, EANN.

MVDroid: an android malicious VPN detector using neural networks

Michalis Pavlidis, Nikolaos Polatidis, S. Khodambashi, 2023, Neural Computing & Applications.

TrojanDroid: Android Malware Detection for Trojan Discovery Using Convolutional Neural Networks

Michalis Pavlidis, Nikolaos Polatidis, Saeed Seraj, 2022, International Conference on Engineering Applications of Neural Networks.

Mobile recommender systems: An overview of technologies and challenges

Nikolaos Polatidis, Christos K. Georgiadis, C. Georgiadis, 2013, 2013 Second International Conference on Informatics & Applications (ICIA).

SEADer: A Social Engineering Attack Detection Method Based on Natural Language Processing and Artificial Neural Networks

Nikolaos Polatidis, Stelios Kapetanakis, Merton Lansley, 2019, ICCCI.

Long-Range attack detection on permissionless blockchains using Deep Learning

Olanrewaju Sanda, Michalis Pavlidis, Nikolaos Polatidis, 2023, Expert systems with applications.

A deep learning approach for host-based cryptojacking malware detection

Olanrewaju Sanda, Michalis Pavlidis, Nikolaos Polatidis, 2023, Evolutionary Systematics.

Cyber-attack path discovery in a dynamic supply chain maritime risk management system

Haralambos Mouratidis, Nikolaos Polatidis, Michalis Pavlidis, 2018, Comput. Stand. Interfaces.

A switching multi-level method for the long tail recommendation problem

Miltos Petridis, Gharbi Alshammari, Jose L. Jorro-Aragoneses, 2019, J. Intell. Fuzzy Syst..

An explanation-based approach for experiment reproducibility in recommender systems

E. Pimenidis, L. Iliadis, Nikolaos Polatidis, 2019, Neural Computing and Applications.

SFA Referee Allocation Scheme pdf

Nikolaos Polatidis, Nikolaos Polatidis, 2014, ArXiv.

DeepKAF: A Heterogeneous CBR & Deep Learning Approach for NLP Prototyping

Nikolaos Polatidis, Stelios Kapetanakis, Klaus-Dieter Althoff, 2020, 2020 International Conference on INnovations in Intelligent SysTems and Applications (INISTA).

A Switching Approach that Improves Prediction Accuracy for Long Tail Recommendations

Miltos Petridis, Gharbi Alshammari, Nikolaos Polatidis, 2019, IntelliSys.

A Method for Privacy-preserving Collaborative Filtering Recommendations

Haralambos Mouratidis, Nikolaos Polatidis, Elias Pimenidis, 2017, J. Univers. Comput. Sci..

A Novel Dataset for Fake Android Anti-Malware Detection

Saeed Seraj, Michalis Pavlidis, Nikolaos Polatidis, 2020, WIMS.

An evaluation of keyword, string similarity and very shallow syntactic matching for a university admissions processing infobot

Nikolaos Polatidis, Peter J. Hancox, Peter Hancox, 2013, Comput. Sci. Inf. Syst..

SEADer++: social engineering attack detection in online environments using machine learning

Nikolaos Polatidis, Stelios Kapetanakis, Francois Mouton, 2020, Journal of Information and Telecommunication.

SEADer++ v2: Detecting Social Engineering Attacks using Natural Language Processing and Machine Learning

Nikolaos Polatidis, Stelios Kapetanakis, Merton Lansley, 2020, 2020 International Conference on INnovations in Intelligent SysTems and Applications (INISTA).

A Guideline-Based Approach for Assisting with the Reproducibility of Experiments in Recommender Systems Evaluation

Andrew Fish, Nikolaos Polatidis, Stelios Kapetanakis, 2019, Int. J. Artif. Intell. Tools.

Reproduction of Experiments in Recommender Systems Evaluation Based on Explanations

Nikolaos Polatidis, Elias Pimenidis, E. Pimenidis, 2018, EANN.

Reproducibility of Experiments in Recommender Systems Evaluation

Nikolaos Polatidis, Stelios Kapetanakis, Elias Pimenidis, 2018, AIAI.

Privacy-preserving collaborative recommendations based on random perturbations

C. Georgiadis, E. Pimenidis, H. Mouratidis, 2017, Expert Syst. Appl..

Recommendations in mobile commerce environments: supporting quality and privacy requirements

Νικόλαος Πολατίδης, Nikolaos Polatidis, 2017 .

Recommender Systems: The Importance of Personalization in E-Business Environments

Nikolaos Polatidis, Christos K. Georgiadis, C. Georgiadis, 2013, Int. J. E Entrepreneurship Innov..