@conference {4657,
	title = {A Chatbot Generator for Improved Digital Governance},
	booktitle = {20th European Mediterranean \& Middle Eastern Conference on Information Systems (EMCIS 2023), December 11 {\textendash} 12, 2023, Dubai, UAE,},
	year = {2023},
	pages = {123-134},
	abstract = {Chatbots, the pioneering conversational artificial intelligence (AI) agents, have experienced remarkable growth and integration in various domains. In modern societies, chatbots have emerged as transformative digital entities, revolutionizing the way humans interact with technology. These conversational AI agents have transcended their initial applications to become integral parts of various industries and daily life. One of the most prominent roles of chatbots is in customer service, where they offer round-the-clock assistance, swift issue resolution, and personalized interactions.By handling routine queries and tasks, chatbots free up human agents to focus on complex and specialized issues, thus optimizing overall efficiency and customer satisfaction. To this end, this paper aims to present and describe the architecture of a novel chatbot generator with improved functionality in terms of quality of communication with end users and level of provided services, with a specialized infrastructure understanding the Greek language. The chatbot generator was developed in the framework of a research project and will
be pilot tested by two end-users, the National Bank of Greece (NBG) and the General Secretariat for Information Systems \& Digital Governance (GSIS-DG).},
	author = {Christos Bouras and Damianos Diasakos and Chrysostomos Katsigiannis and Vasileios Kokkinos and Apostolos Gkamas and Nikos Karacapilidis and Yannis Charalabidis and Zoi Lachana and Charalampos Alexopoulos and Theodoros Papadopoulos and Georgios Karamanolis and Michail Psalidas}
}
@conference {4658,
	title = {Chatbot technology asseeement: 40 cases from Greece},
	booktitle = {20th European Mediterranean \& Middle Eastern Conference on Information Systems (EMCIS 2023), December 11 {\textendash} 12, 2023, Dubai, UAE,},
	year = {2023},
	pages = {167-181},
	abstract = {In recent years, the field of Artificial Intelligence has seen significant progress, particularly in the development of chatbots via Natural Language Processing (NLP) technology. Recently, however, there has been a real race in this sector with major technology companies constantly presenting new improved solutions. However, the Greek reality presents several peculiarities and difficulties in adopting modern solutions, both due to the diosyncrasies and rarity of the language and the limited funding capabilities of the Greek economy. The purpose of this research is to evaluate the performance of chatbots in terms of the quality of their responses regarding relevance, naturalness, cohesion, accuracy, vocabulary, as well as to assess the user experience and satisfaction. Another goal is to gain a comprehensive comparative picture of chatbot operation in Greece, both
per question and in comparison, between relevant questions. A guided interview with closed-type questions was chosen as the method of evaluation. The aim is to obtain structured and quantified data in an area where the average internet user is not fully familiarized and does not have previous relevant evaluation experience. Conclusions were drawn per question in order to evaluate the level of solutions in a focused and comparative way to identify possible trends and to confirm the consistency of the responses.},
	author = {Yannis Charalabidis and Thanos Anagnou and Charalampos Alexopoulos and Theodoros Papadopoulos and Zoi Lachana and Christos Bouras and Nikos Karacapilidis and Vasileios Kokkinos and Apostolos Gkamas}
}
@conference {4655,
	title = {On the Development of a Novel Chatbot Generator Architecture: Design and Assessment Issues},
	booktitle = {8th IEEE International Conference on Mathematics and Computers in Sciences (MCSI 2023), October 14 - 16, 2023, Athens, Greece},
	year = {2023},
	abstract = {Chatbots are witnessing remarkable growth in various fields. In modern society, chatbots have evolved into innovative digital entities that have revolutionized the way people interact with technology. These conversational AI agents have gone beyond their initial uses to become an integral part of various industries. One of the most important roles of chatbots is customer service, providing 24/7 support, quick problem resolution, and personalized interactions. Chatbots free up human agents by handling routine queries and tasks, allowing them to focus on complex and specific issues, optimizing the overall efficiency and customer satisfaction. To this end, this paper aims to present the architecture of a novel chatbot generator with improved functionality in terms of quality of communication with end users and level of provided services. In addition, the paper presents the results of two pilot chatbots assessment by users with experience in artificial intelligence and chatbot technology.},
	author = {Christos Bouras and Damianos Diasakos and Chrysostomos Katsigiannis and Vasileios Kokkinos and Apostolos Gkamas and Nikos Karacapilidis and Yannis Charalabidis and Zoi Lachana and Charalampos Alexopoulos and Theodoros Papadopoulos and Georgios Karamanolis and Michail Psalidas}
}
@inbook {4497,
	title = {An agent-based simulation model for energy saving in large passenger and cruise ships},
	booktitle = {CRC Press},
	year = {2021},
	abstract = {Undoubtedly, energy saving is of paramount importance in the shipping industry, as far as both the protection of environment and the reduction of the associated operating costs are concerned. In this direction, the
International Maritime Organization aims to reduce ship emissions by at least 50\% by 2050, while ships to be built by 2025 are expected to be a massive 30\% more energy efficient than those built some years ago [IMO,
2018].},
	author = {Christos Bouras and Eirini Barri and Apostolos Gkamas and Nikos Karacapilidis and Dimitris Karadimas and Giorgos Kournetas and Yiannis Panaretou}
}
@inbook {4498,
	title = {A Novel Approach to Energy Management in Large Passenger and Cruise Ships: Integrating Simulation and Machine Learning Models},
	booktitle = {Springer Book of SIMULTECH 2020},
	year = {2021},
	abstract = {It has been broadly admitted that the prediction of energy consumption in large passenger and cruise ships is a complex and challenging issue. Aiming to address it, this chapter reports on the development of a novel approach that builds on a sophisticated agent-based simulation model, which takes into account diverse parameters such as the size, type and behavior of the different categories of passengers onboard, the energy consuming facilities and devices of a ship, spatial data concerning the layout of a ship{\textquoteright}s decks, and alternative ship operation modes. According to the proposed approach, outputs obtained from multiple simulation runs are then exploited by prominent Machine Learning algorithms to extract meaningful patterns between the composition of passengers and the corresponding energy demands in a ship. In this way, our approach is able to predict alternative energy consumption scenarios and trigger meaningful insights concerning the overall energy management in a ship. Overall, the proposed approach may handle the underlying uncertainty by blending the process centric character of a simulation model and the data-centric character of Machine Learning algorithms. The chapter also describes the overall architecture of the proposed solution, which is based on the microservices approach.},
	author = {Christos Bouras and Eirini Barri and Apostolos Gkamas and Nikos Karacapilidis and Dimitris Karadimas and Georgios Kournetas and Yiannis Panaretou}
}
@conference {4457,
	title = {Blending simulation and Machine Learning models to advance energy management in large ships},
	booktitle = {10th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2020)},
	year = {2020},
	pages = {101-109},
	abstract = {The prediction of energy consumption in large passenger and cruise ships is certainly a complex and challenging issue. Towards addressing it, this paper reports on the development of a novel approach that builds on a sophisticated agent-based simulation model, which takes into account diverse parameters such as the size, type and behavior of the different categories of passengers onboard, the energy consuming facilities and devices of a ship, spatial data concerning the layout of a ship{\textquoteright}s decks, and alternative ship operation modes. Outputs obtained from multiple simulation runs are then exploited by prominent Machine Learning algorithms to extract meaningful patterns between the composition of passengers and the corresponding energy demands in a ship. In this way, our approach is able to predict alternative energy consumption scenarios and trigger meaningful insights concerning the overall energy management in a ship. Overall, the proposed approach may handle the underlying uncertainty by blending the process-centric character of a simulation model and the data-centric character of Machine Learning algorithms.},
	author = {Eirini Barri and Christos Bouras and Apostolos Gkamas and Nikos Karacapilidis and Dimitris Karadimas and Georgios Kournetas and Yiannis Panaretou}
}
@conference {4460,
	title = {A Novel Approach for Handling Diverse Energy Consumption Issues in Large Passenger and Cruise Ships},
	booktitle = {7th International Conference on Energy, Substainability and Climate Change (ESCC 2020), Skiathos, Greece},
	year = {2020},
	abstract = {The prediction of energy consumption in large passenger and cruise ships is certainly a complex and challenging issue. Towards addressing it, this paper reports on the development of a novel approach that builds on a sophisticated agent-based simulation model, which takes into account diverse parameters such as the size, type and behavior of the different categories of passengers onboard, the energy consuming facilities and devices of a ship, spatial data concerning the layout of a ship{\textquoteright}s decks, and alternative ship operation modes. Outputs obtained from multiple simulation runs are then exploited by prominent Machine Learning algorithms to extract meaningful patterns between the composition of passengers and the corresponding energy demands in a ship. In this way, our approach is able to predict alternative energy consumption scenarios and trigger meaningful insights concerning the overall energy management in a ship. Overall, the proposed approach may handle the underlying uncertainty by blending the process-centric character of a simulation model and the data-centric character of Machine Learning algorithms.},
	author = {Eirini Barri and Christos Bouras and Apostolos Gkamas and Georgios Kournetas and Nikos Karacapilidis}
}
@conference {4463,
	title = {Towards an informative simulation-based application for energy saving in large passenger and cruise ships},
	booktitle = {6th IEEE International Energy Conference (ENERGYCon 2020), Gammarth, Tunisia},
	year = {2020},
	abstract = {Over the years, the need to save energy and efficiently manage its consumption becomes increasingly imperative. This paper reports on the development of a novel application for handling diverse energy consumption issues in large passenger and cruise ships. Our overall approach is based on a comprehensive agent-based simulation model, which takes into account spatial data concerning a ship{\textquoteright}s decks and position of energy consuming facilities, as well as data concerning the ship{\textquoteright}s passengers and their behavior during the operation of the vessel. The proposed application may predict energy consumption for a particular vessel and passenger group and accordingly facilitate informed decision making on energy saving matters.},
	author = {Eirini Barri and Christos Bouras and Apostolos Gkamas and Nikos Karacapilidis and Dimitris Karadimas and Georgios Kournetas and Yiannis Panaretou}
}
@conference {4115,
	title = {A Mobile Learning Application for Self-Management of Health and Disease},
	booktitle = {2015 International Conference on Interactive Mobile Communication Technologies and Learning, Thessaloniki, Greece},
	year = {2015},
	month = {November 19 - 20},
	pages = {101-105},
	abstract = {<p class="rtejustify">Supporting self-management of patients is a highly challenging task, which needs to meaningfully exploit and interrelate approaches and technologies concerning interactive communication, personalized health and mobile learning. In line with these remarks, this paper reports on the development of an innovative clinical decision support platform for selfmanagement of health and disease purposes. Work presented focuses on two basic components of the platform, namely a webbased collaboration support tool and a mobile application, both aiming to augment the interaction of all types of stakeholders with the platform. The functionality of the above components is sketched through a realistic use case.</p>
},
	author = {Christos Bouras and Vaggelis Kapoulas and Nikos Karacapilidis and Vasileios Kokkinos and Andreas Papazois}
}
