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150 results on '"Tsekouras, George E."'

1. ChatGPT and Persuasive Technologies for the Management and Delivery of Personalized Recommendations in Hotel Hospitality

Author

Remountakis, Manolis, Kotis, Konstantinos, Kourtzis, Babis, and Tsekouras, George E.

Subjects
Computer Science - Information Retrieval, Computer Science - Artificial Intelligence, Computer Science - Computation and Language, Computer Science - Machine Learning, 68T01, I.2.1
Abstract

Recommender systems have become indispensable tools in the hotel hospitality industry, enabling personalized and tailored experiences for guests. Recent advancements in large language models (LLMs), such as ChatGPT, and persuasive technologies, have opened new avenues for enhancing the effectiveness of those systems. This paper explores the potential of integrating ChatGPT and persuasive technologies for automating and improving hotel hospitality recommender systems. First, we delve into the capabilities of ChatGPT, which can understand and generate human-like text, enabling more accurate and context-aware recommendations. We discuss the integration of ChatGPT into recommender systems, highlighting the ability to analyze user preferences, extract valuable insights from online reviews, and generate personalized recommendations based on guest profiles. Second, we investigate the role of persuasive technology in influencing user behavior and enhancing the persuasive impact of hotel recommendations. By incorporating persuasive techniques, such as social proof, scarcity and personalization, recommender systems can effectively influence user decision-making and encourage desired actions, such as booking a specific hotel or upgrading their room. To investigate the efficacy of ChatGPT and persuasive technologies, we present a pilot experi-ment with a case study involving a hotel recommender system. We aim to study the impact of integrating ChatGPT and persua-sive techniques on user engagement, satisfaction, and conversion rates. The preliminary results demonstrate the potential of these technologies in enhancing the overall guest experience and business performance. Overall, this paper contributes to the field of hotel hospitality by exploring the synergistic relationship between LLMs and persuasive technology in recommender systems, ultimately influencing guest satisfaction and hotel revenue., Comment: 17 pages, 12 figures

Published
2023

2. Ontology-based Feature Selection: A Survey

Author

Sikelis, Konstantinos, Tsekouras, George E, and Kotis, Konstantinos I

Subjects
Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

The SemanticWeb emerged as an extension to the traditional Web, towards adding meaning to a distributed Web of structured and linked data. At its core, the concept of ontology provides the means to semantically describe and structure information and data and expose it to software and human agents in a machine and human-readable form. For software agents to be realized, it is crucial to develop powerful artificial intelligence and machine learning techniques, able to extract knowledge from information and data sources and represent it in the underlying ontology. This survey aims to provide insight into key aspects of ontology-based knowledge extraction, from various sources such as text, images, databases and human expertise, with emphasis on the task of feature selection. First, some of the most common classification and feature selection algorithms are briefly presented. Then, selected methodologies, which utilize ontologies to represent features and perform feature selection and classification, are described. The presented examples span diverse application domains, e.g., medicine, tourism, mechanical and civil engineering, and demonstrate the feasibility and applicability of such methods., Comment: 25 pages

Published
2021

7. Modeling Data Center Temperature Profile in Terms of a First Order Polynomial RBF Network Trained by Particle Swarm Optimization

Author

Troumbis, Ioannis A., Tsekouras, George E., Kalloniatis, Christos, Papachiou, Panagiotis, Haralambopoulos, Dias, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Kůrková, Věra, editor, Manolopoulos, Yannis, editor, Hammer, Barbara, editor, Iliadis, Lazaros, editor, and Maglogiannis, Ilias, editor

Published
2018
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8. Evaluating Ontology-Based PD Monitoring and Alerting in Personal Health Knowledge Graphs and Graph Neural Networks.

Author

Zafeiropoulos, Nikolaos, Bitilis, Pavlos, Tsekouras, George E., and Kotis, Konstantinos

Subjects
GRAPH neural networks, KNOWLEDGE graphs, HEALTH literacy, MEDICAL records, MEDICAL care
Abstract

In the realm of Parkinson's Disease (PD) research, the integration of wearable sensor data with personal health records (PHR) has emerged as a pivotal avenue for patient alerting and monitoring. This study delves into the complex domain of PD patient care, with a specific emphasis on harnessing the potential of wearable sensors to capture, represent and semantically analyze crucial movement data and knowledge. The primary objective is to enhance the assessment of PD patients by establishing a robust foundation for personalized health insights through the development of Personal Health Knowledge Graphs (PHKGs) and the employment of personal health Graph Neural Networks (PHGNNs) that utilize PHKGs. The objective is to formalize the representation of related integrated data, unified sensor and PHR data in higher levels of abstraction, i.e., in a PHKG, to facilitate interoperability and support rule-based high-level event recognition such as patient's missing dose or falling. This paper, extending our previous related work, presents the Wear4PDmove ontology in detail and evaluates the ontology within the development of an experimental PHKG. Furthermore, this paper focuses on the integration and evaluation of PHKG within the implementation of a Graph Neural Network (GNN). This work emphasizes the importance of integrating PD-related data for monitoring and alerting patients with appropriate notifications. These notifications offer health experts precise and timely information for the continuous evaluation of personal health-related events, ultimately contributing to enhanced patient care and well-informed medical decision-making. Finally, the paper concludes by proposing a novel approach for integrating personal health KGs and GNNs for PD monitoring and alerting solutions. [ABSTRACT FROM AUTHOR]

Published
2024
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11. Neuro-Fuzzy Network for Modeling the Shoreline Realignment of the Kamari Beach, Santorini, Greece

Author

Tsekouras, George E., Trygonis, Vasilis, Rigos, Anastasios, Chatzipavlis, Antonios, Tsolakis, Dimitrios, Velegrakis, Adonis F., Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Boracchi, Giacomo, editor, Iliadis, Lazaros, editor, Jayne, Chrisina, editor, and Likas, Aristidis, editor

Published
2017
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14. Feature Selection with a Backtracking Search Optimization Algorithm

Author

Sikelis Konstantinos and Tsekouras George E.

Subjects
index terms, backtracking search optimization, feature selection, binary search, set-based search, Information technology, T58.5-58.64
Abstract

Feature selection carries significance in the outcome of any classification or regression task. Exercising evolutionary computation algorithms in feature selection has led to the construction of efficient discrete optimization algorithms. In this paper, a modified backtracking search algorithm is employed to perform wrapper-based feature selection, where two modifications of the standard backtracking search algorithm are adopted. The first one concentrates on utilizing a particle ranking operator regarding the current population. The second one focuses on removing the case of using a single particle on the mutation process. Then, the implementation of the above algorithm in feature selection is carried out in terms of two general frameworks, which originally were developed for the particle swarm optimization. The first framework is based on the binary and the second on the set-based particle swarm optimization. The experimental analysis shows that the above variants of the backtracking search algorithm perform equally well on the classification of several datasets.

Published
2022
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15. Modeling Beach Rotation Using a Novel Legendre Polynomial Feedforward Neural Network Trained by Nonlinear Constrained Optimization

Author

Rigos, Anastasios, Tsekouras, George E., Chatzipavlis, Antonios, Velegrakis, Adonis F., Rannenberg, Kai, Editor-in-chief, Sakarovitch, Jacques, Series editor, Goedicke, Michael, Series editor, Tatnall, Arthur, Series editor, Neuhold, Erich J., Series editor, Pras, Aiko, Series editor, Tröltzsch, Fredi, Series editor, Pries-Heje, Jan, Series editor, Whitehouse, Diane, Series editor, Reis, Ricardo, Series editor, Furnell, Steven, Series editor, Furbach, Ulrich, Series editor, Gulliksen, Jan, Series editor, Rauterberg, Matthias, Series editor, Iliadis, Lazaros, editor, and Maglogiannis, Ilias, editor

Published
2016
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18. A Neural-Fuzzy Network Based on Hermite Polynomials to Predict the Coastal Erosion

Author

Tsekouras, George E., Rigos, Anastasios, Chatzipavlis, Antonios, Velegrakis, Adonis, Diniz Junqueira Barbosa, Simone, Series editor, Chen, Phoebe, Series editor, Du, Xiaoyong, Series editor, Filipe, Joaquim, Series editor, Kara, Orhun, Series editor, Kotenko, Igor, Series editor, Liu, Ting, Series editor, Sivalingam, Krishna M., Series editor, Washio, Takashi, Series editor, Iliadis, Lazaros, editor, and Jayne, Chrisina, editor

Published
2015
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31. A Fuzzy Logic-Based Approach for Detecting Shifting Patterns in Cross-Cultural Data

Author

Tsekouras, George E., Papageorgiou, Dimitris, Kotsiantis, Sotiris B., Kalloniatis, Christos, Pintelas, Panagiotis, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Carbonell, Jaime G., editor, Siekmann, Jörg, editor, Ali, Moonis, editor, and Esposito, Floriana, editor

Published
2005
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