List of publications

 

Publications in Int'l Journals

1.    D. Karapiperis, C. Tjortjis, V.S. Verykios, 'A Suite of Efficient Randomized Algorithms for Streaming Record Linkage', IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024 (IEEE), Scimago Q1.

2. N. Tsalikidis, A. Mystakidis, P. Koukaras, M. Ivaškevičius, L. Morkūnaitė, D. Ioannidis, P.A. Fokaides, C. Tjortjis, D. Tzovaras, 'Urban traffic congestion prediction A multi-step approach utilizing sensor data and weather information', Smart Cities, Vol. 7, No. 1, pp. 233–253. 2024, (MDPI), Scimago Q1.

3. V. Sarlis, D. Gerakas, C. Tjortjis, ' A Data Science and Sports Analytics Approach to Decode Clutch Dynamics in the Last-Minutes of NBA Games', Machine Learning and Knowledge Extraction, 6(3), pp. 2074–2095. 2024 (MDPI), Scimago Q1.

4. C. Markopoulou, G. Papageorgiou, C. Tjortjis, 'Diverse Machine Learning for Forecasting Goal-Scoring Likelihood in Elite Football Leagues', Machine Learning and Knowledge Extraction, 2024, (MDPI), Scimago Q1

5. N. Tsalikidis, A. Mystakidis, C. Tjortjis, P. Koukaras, D. Ioannidis, 'Energy Load Forecasting: One-Step Ahead Hybrid Model utilizing ensembling', Computing, Vol. 106, No. 1, pp. 241-273, 2024, (Springer), Scimago Q2.

6. A. Mystakidis, C. Tjortjis, 'Traffic congestion prediction with missing data: a Classification approach using weather information', Int’l Journal of Data Science and Analytics, 2024, (Springer), Scimago Q2.

7. G. Papageorgiou, V. Sarlis, C. Tjortjis, 'An Innovative Method for Accurate NBA Player Performance Forecasting and Line-up Optimization in Daily Fantasy Sports', Int’l Journal of Data Science and Analytics, 2024, (Springer), Scimago Q2

8. A. Kousis, C. Tjortjis, 'Investigating the key aspects of a smart city through topic modeling and thematic analysis', Future Internet, Vol. 16, No. 1: 3. 2024, (MDPI), Scimago Q2.

9. P. Koukaras, K. Afentoulis, P. Gkaidatzis, A. Mystakidis, D. Ioannidis, S. Vagropoulos and C. Tjortjis. 'Integrating Blockchain in Smart Grids for Enhanced Demand Response: Challenges, Strategies, and Future Directions', Energies, 2024, (MDPI), Scimago Q1.

10. A. Mystakidis, P. Koukaras, N. Tsalikidis, D. Ioannidis and C. Tjortjis, 'Energy Forecasting: A Comprehensive Review of Techniques and Technologies', Energies, 17, 1662, 2024, (MDPI), Scimago Q1.

11. P. Koukaras, A. Mustapha, A. Mystakidis, and C. Tjortjis, 'Optimizing Building Short-Term Load Forecasting A Comparative Analysis of Machine Learning Models', Energies, 17, 1450, 2024, (MDPI), Scimago Q1.

12. 1. M. Tsiourlini, K. Tzafilkou, D. Karapiperis, C. Tjortjis, 'Text Analytics on YouTube Comments for Food Products', Information, 2024, (MDPI), Scimago Q2

13. 2. G. Papageorgiou, V. Sarlis, M. Maragoudakis, C. Tjortjis, ' Enhancing E-Government Services through a state of the art, modular and reproducible architecture over Large Language Models', Applied Sciences, 14(18), 8259; 2024, (MDPI), Scimago Q2.

14. V. Sarlis, C. Tjortjis, ' Sports Analytics: Data Mining to uncover NBA Player Position, Age, and Injuries Impact on Performance and Economics', Information, 15(4), 242; (MDPI), Scimago Q2.

15. G. Papageorgiou, V. Sarlis, C. Tjortjis, 'Unsupervised Learning in NBA Injury Recovery: Advanced Data Mining to Decode Recovery Durations and Economic Impacts', Information, Vol. 15, No. 1, 61, 2024, (MDPI), Scimago Q2.

16. G. Papageorgiou, D. Gkaimanis, C. Tjortjis, ' Enhancing Stock Market Forecasts with Double Deep Q-Network in Volatile Stock Market Environments', Electronics, 13(9), 1629; 2024, (MDPI), Scimago Q2.

17. G. Papageorgiou, V. Sarlis, C. Tjortjis, 'Evaluating the Effectiveness of Machine Learning Models for Performance Forecasting in Basketball: A Comparative Study', Knowledge and Information Systems, 2024, (Springer), Scimago Q2.

18. V. Sarlis, G. Papageorgiou, C. Tjortjis, 'Leveraging Sports Analytics and Association Rule Mining to Uncover Recovery and Economic Impacts in NBA Basketball', Data, 9(83). 2024, (MDPI), Scimago Q2.

19. K.V. Tompra, G. Papageorgiou, C. Tjortjis, ' Strategic Machine Learning Optimization for Cardiovascular Disease Prediction and High-Risk Patient Identification', Algorithms, 17(5), 178; 20224, (MDPI), Scimago Q2.

20. V. Sarlis, G. Papageorgiou, C. Tjortjis, 'Injury Patterns and Impact on Performance in the NBA League using Sports Analytics', Computation, Vol. 12, No. 2, 36. 2024, (MDPI), Scimago Q2.

21. F. Shaban, P. Siskos and C. Tjortjis, 'Electromobility prospects in Greece by 2030: a regional perspective on strategic policy analysis' Energies, Vol. 16, No. 16, 6083, 2023, (MDPI), Scimago Q1.

22. M.T. Siddique, P. Koukaras, D. Ioannidis, C. Tjortjis, 'A Methodology Integrating Quantitative As-sessment of Energy Efficient Operation and Occupant needs into the Smart Readiness Indicator', Energies, Vol. 16, No. 19, 7007; 2023, (MDPI), Scimago Q1.

23. A. Mystakidis, E. Ntozi, K. Afentoulis, P. Koukaras, P. Gkaidatzis, D. Ioannidis, C. Tjortjis and D. Tzovaras, 'Energy generation forecasting: Elevating performance with machine and deep learning', Computing, Vol. 105, pp. 1623–1645, 2023, (Springer), Scimago Q2.

24. P. Koukaras, D. Rousidis and C. Tjortjis, 'Unraveling Microblog Sentiment Dynamics: A Twitter Public Attitudes Analysis Towards COVID-19 Cases and Deaths', Informatics, Vol. 10, No. 4, 88, 2023, (MDPI), Scimago Q2.

25. I. Chalikias, K. Tzafilkou, D. Karapiperis, C. Tjortjis, 'Learning Analytics on YouTube Educational Videos: Exploring Sentiment Analysis and Topic Clustering Methods', Electronics, 2023, (MDPI), Scimago Q2.

26. V. Sarlis, G. Papageorgiou, C. Tjortjis, 'Sports Analytics and Text Mining NBA Data to Assess Recovery from Injuries and their Economic Impact', Computers, Vol. 12, No. 12, 261, 2023, (MDPI), Scimago Q2.

27. M.T. Siddique, P. Koukaras, D. Ioannidis, C. Tjortjis, 'SmartBuild RecSys: A Recommendation System based on the Smart Readiness Indicator for Energy Efficiency in Buildings', Algorithms,, Vol. 16, No. 10, 482, 2023 (MDPI), Scimago Q2.

28. N. Stasinos, A. Kousis, V. Sarlis, A. Mystakidis, D. Rousidis, P. Koukaras, I. Kotsiopoulos, C. Tjortjis, 'A Tri-model Prediction Approach for COVID-19 ICU Bed Occupancy: A Case Study', Algorithms, Vol. 16, No. 3: 140, 2023, (MDPI), Scimago Q2.

29. D. P. Kasseropoulos, P. Koukaras and C. Tjortjis, 'Exploiting textual information for fake news detection', Int’l Journal of Neural Systems, Vol. 32, No. 12, 2022, (World Scientific Publishing), Scimago Q1.

30. P. Koukaras, C. Tjortjis and D. Rousidis, 'Mining Association Rules from COVID-19 Related Twitter Data to Discover Word Patterns, Topics and Inferences', Information Systems, p. 102054, 2022, (Elsevier), Scimago Q2.

31. P. Koukaras, C. Tjortjis, P. Gkaidatzis, N. Bezas, D. Ioannidis, and D. Tzovaras, 'A Multidisciplinary Approach on Efficient Virtual Microgrid to Virtual Microgrid Energy Balancing Incorporating Data Preprocessing Techniques', Computing, (Springer This is a post-peer-review, pre-copyedit version of an article published in Computing.), Vol. 104, No. 1, pp. 209-250, 2022, Scimago Q2.

32. P. Koukaras, C. Nousi and C. Tjortjis, 'Stock Market Prediction Using Microblogging Sentiment Analysis and Machine Learning', Telecom, 3(2), 358-378, 2022, (MDPI), Scimago Q2.

33. S. Liapis, K. Christantonis, V. Chazan-Pantzalis, A. Manos, D.E. Filippidou, and C. Tjortjis, 'A methodology using classification for traffic prediction: Featuring the impact of COVID-19', Integrated Computer-Aided Engineering (ICAE), ), Vol. 28, pp. 417-435, 2021, (IOS Press), Scimago Q1.

34. P. Koukaras, N. Bezas, P. Gkaidatzis, D. Ioannidis, D. Tzovaras, and C. Tjortjis, 'Introducing a Novel Approach in One-step Ahead Energy Load Forecasting', Sustainable Computing: Informatics and Systems, Vol. 32, 2021, (Elsevier), Scimago Q1.

35. V. Sarlis, V. Chatziilias, C. Tjortjis, D. Mandalidis, 'A Data Science Approach Analysing the Impact of Injuries on Basketball Players and Team Performance', Information Systems, Vol. 93, 2021, (Elsevier), Scimago Q1.

36. P. Koukaras, P. Gkaidatzis, N. Bezas, T. Bragatto, M. Antal, F. Carere, D. Ioannidis, C. Tjortjis and D. Tzovaras, 'A Tri-layer Optimization Framework for One-day Ahead Energy Scheduling based on Cost and Discomfort Minimization', Energies, Vol. 14, no 12, 3599; 2021, (MDPI), Scimago Q1.

37. A. Kousis and C. Tjortjis, 'Data Mining Algorithms for Smart Cities: A Bibliometric Analysis', Algorithms, Vol. 14, no. 8, 242, 2021, (MDPI), Scimago Q2..

38. A. Mystakidis, N. Stasinos, A. Kousis, V. Sarlis, P. Koukaras, D. Rousidis, I. Kotsiopoulos, C. Tjortjis, 'Predicting Covid-19 ICU needs using Deep Learning, XGBoost and Random Forest Regression with the Sliding Window technique', IEEE Smart Cities, July 2021.

39 P. Koukaras, D. Rousidis and C. Tjortjis, 'Introducing a novel Bi-functional method for Exploiting Sentiment in Complex Information Networks', Int’l Journal of Metadata, Semantics and Ontologies. , 2021, (Inderscience), Scimago Q2.

40. V. Sarlis, C. Tjortjis, 'Sports Analytics – Evaluation of Basketball Players and Team Performance', Information Systems, 93, 101562, 2020, (Elsevier) Scimago Q1.

41. Tjortjis C., 'Mining Association Rules from Code (MARC) to Support Legacy Software Management ', (Springer. This is a post-peer-review, pre-copyedit version of an article published in Software Quality Journal. The final authenticated version is available online), 28(2), 633-662, 2020, Scimago Q2.

42.     K. Christantonis, C. Tjortjis, A. Manos, D Filippidou and E. Christelis, 'Smart Cities Data Classification for Electricity Consumption & Traffic Prediction', Automatics & Software Enginery, 31(1), 2020.

43.     Rousidis D., Koukaras P., Tjortjis C., 'Social Media Prediction A Literature Review', (Springer. Multimedia Tools and Applications. The final authenticated version is available online), 79(9), 6279-6311, 2020, Scimago Q1.

44.     Koukaras P., Tjortjis C., Rousidis D., 'Social Media Types: Introducing a Data Driven Taxonomy', (Springer. This is a post-peer-review, pre-copyedit version of an article published in Computing. The final authenticated version is available online), Vol. 102, no. 1, pp. 295-340, 2020, Scimago Q2.

45.     Ghafari, S.M.; Tjortjis, C. 'A Survey on Association Rules Mining Using Heuristics', WIREs Data Mining and Knowledge Discovery, Vol. 9, no. 4, July/August 2019, (Wiley). Scimago Q1.

46.     Koubarakis M., Vouros G., Chalkiadakis G., Plagianakos V., Tjortjis C., Kavallieratou E., Vrakas D., Mavridis N., Petasis G., Blekas K., Krithara A., 'AI in Greece: The Case of Research on Linked Geospatial Data' the AI magazine, Vol 39, No 2, pp. 91-96, Summer 2018, (AAAI). Scimago Q2.

47.     Tzirakis P. and Tjortjis C., 'T3C: Improving a Decision Tree Classification Algorithm's Interval Splits on Continuous Attributes', Advances in Data Analysis and Classification, Vol. 11, No. 2, pp. 353-370, 2017, (Springer), ISSN 1862-5347. Scimago Q1. Executable version of T3C. To execute use: /T3C -f data/heart -m 0.2 -u (-m sets the Maximum Acceptable Error. For help use:./T3C -h)

48.     Tatsis V.A., Tjortjis C., Tzirakis P., 'Evaluating data mining algorithms using molecular dynamics trajectories', Int'l Journal of Data Mining and Bioinformatics (IJDMB), Vol. 8, No. 2, pp. 169-187, 2013, (Inderscience), ISSN: 1748-5673. Scimago Q3.

49.     Kanellopoulos Y., Antonellis P., Tjortjis C. Makris C. and Tsirakis N., 'k-Attractors: A Partitional Clustering Algorithm for Numeric Data analysis', Applied Artificial Intelligence, Vol. 25 No.2, pp. 97-115, 2011, (Taylor & Francis) ISSN: 0883-9514. Scimago Q3.

50 Kanellopoulos Y., Antonellis P., Antoniou D., Makris C., Theodoridis E., Tjortjis C., Tsirakis N., 'Code Quality Evaluation methodology using the ISO/IEC 9126 Standard', Int’l Journal of Software Engineering & Applications, Vol.1, No.2, pp. 17-36, 2010, (AIRCC), ISSN 0976-2221. Most cited article for 2010.

51.  Denaxas S. and Tjortjis C., 'A GO-driven semantic similarity measure for quantifying the biological relatedness of gene products', Intelligent Decision Technologies, Vol. 3, No 4, pp. 239-248, 2009, (IOS Press), ISSN: 1872-4981. Scimago Q3.

52.  Zhang S., Tjortjis C., Zeng X., Qiao H., Buchan I., and Keane J., 'Comparing Data Mining Methods with Logistic Regression in Childhood Obesity Prediction', Information Systems Frontiers Journal, Vol. 11, No. 4, pp. 449-460, 2009, (Springer), ISSN 1387-3326. Scimago Q1. 

53.  Antonellis P., Antoniou D., Kanellopoulos Y., Makris C., Theodoridis E., Tjortjis C., Tsirakis N., 'Clustering for Monitoring Software Systems Maintainability Evolution', Electronic Notes in Theoretical Computer Science, Vol. 233, pp. 43-57, March 2009, (Elsevier), ISSN 1571-0661. Scimago Q2

54.  Kontogiannis K., Tjortjis C., and Winter A. (eds.) Editorial for a Special Issue on the 12th Conf. on Software Maintenance and Reengineering (CSMR 2008), Journal of Software Maintenance and Evolution: Research and Practice, Vol. 21, No. 2, pp. 79-80, 2009, (Wiley) ISSN: 1532-060X. Scimago Q2

55.  Denaxas S. and Tjortjis C., 'Scoring and summarizing gene product clusters using the Gene Ontology', Int'l Journal of Data Mining and Bioinformatics, Vol. 2, No. 3, pp.216- 235, 2008, (Inderscience), ISSN 1748-5673. Scimago Q3.

56.  Tjortjis C., Saraee M., Theodoulidis B., Keane J.A, 'Using T3, an Improved Decision Tree Classifier, for Mining Stroke Related Medical Data', Methods of Information in Medicine, Vol. 46, No. 5, pp. 523-529, 2007, (Thieme), ISSN 0026-1270. Scimago Q2. Executable version of T3

57.  Kaldis E., Koukoravas K., and Tjortjis C., 'Re-engineering Academic Teams towards a Network Organizational Structure', Decision Sciences Journal of Innovative Education, Vol. 5 No. 2, pp. 245-266, 2007, (Wiley), ISSN 1540-4595. Scimago Q1.

58.  Kanellopoulos Y., Makris C. and Tjortjis C., 'An Improved Methodology on Information Distillation by Mining Program Source Code', Data & Knowledge Engineering, Vol. 61, No 2, pp. 359-383, 2007, (Elsevier), ISSN 0169-023X. Scimago Q2.

59.   Kanellopoulos Y., Dimopoulos T., Tjortjis C. and Makris C., 'Mining Source Code Elements for Comprehending Object-Oriented Systems and Evaluating Their Maintainability', ACM SIGKDD Explorations, Vol. 8. No. 1, pp. 33-40, 2006, (ACM Press), ISSN 1931-0145.

 

Edited Book

Graph Databases and their use in social media and smart cities, Editor C. Tjortjis, CRC Press, Taylor & Francis Group, 2023 DOI: 10.1201/9781003183532

 

Book chapters

1.   M. Vasileiou, G. Papageorgiou, C. Tjortjis, 'Software defect detection using Machine learning on data from open-source programs', Lecture Notes in Networks and Systems, Springer, 2024.

2. O. Geromichalou, A. Mystakidis, C. Tjortjis, 'Traffic Congestion Prediction: A Machine Learning approach', Lecture Notes in Networks and Systems, Springer, 2024.

3. M. Vlachos Giovanopoulos, G. Michailidis, P. Koukaras and C. Tjortjis, ' Healthcare support using Data Mining: A case study on stroke prediction', Artificial Intelligence and Machine Learning for Healthcare. Intelligent Systems Reference Library Vol. 229, pp. 71-93, Springer, 2023.

4. V. Chouliara, E. Kapoteli, P. Koukaras and C. Tjortjis, ' Social Media Sentiment Analysis related to COVID-19 Vaccinations', Artificial Intelligence and Machine Learning for Healthcare. Intelligent Systems Reference Library Vol. 229, pp. 47–69, Springer, 2023.

5. P. Koukaras, S. Krinidis, D. Ioannidis, C. Tjortjis, and D. Tzovaras, ' Big Data and analytics in the con-text of deep renovation lifecycle', Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham., 2023.

6. C. Nousi, P. Belogianni, P. Koukaras and C. Tjortjis, ' Mining Data to Deal with Epidemics: Case Studies to Demonstrate Real World AI Applications', Handbook of Artificial Intelligence in Healthcare, . Intelligent Systems Reference Library, vol 211, pp. 287-312, Springer, 2022

7. T. Chatzinikolaou, E. Vogiatzi, A. Kousis, C. Tjortjis, ' Smart Healthcare Support Using Data Mining and Machine Learning', IoT and WSN based Smart Cities: A Machine Learning Perspective, EAI/Springer Innovations in Communication and Computing, 2022.

8.   Koukaras P., Rousidis D., Tjortjis C., 'Forecasting and Prevention mechanisms using Social Media in Healthcare', Advanced Computational Intelligence in Healthcare (SCI), vol. 891, pp. 121-137, Springer, 2020.

9. Koukaras P., Tjortjis C., 'Social Media Analytics, types and methodology', Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems, (LAIS), vol. 1, pp. 401-427, Springer, 2019.

 

Referred publications in Springer-Verlag Lecture Notes and ACM Int'l Conf. Proc. Series

1.  P. Koukaras, C. Berberidis, and C. Tjortjis, 'A Semi-supervised Learning Approach for Complex Information Networks', 3rd Int'l Conf. Intelligent Data Communication Technologies and Internet of Things (ICICI 2020) 2020.

2. P. Koukaras, D. Rousidis and C. Tjortjis, ‘An Introduction to Information Network Modeling Capabilities, Utilizing Graphs’, 14th Int’l Conf. Metadata and Semantics Research (MTSR2020), Communications in Computer & Information Science (CCIS), Springer 2020.

3 .D. Rousidis, P. Koukaras and C. Tjortjis, ‘Examination of NoSQL Transition and Data Mining capabilities’, 14th Int’l Conf. Metadata and Semantics Research (MTSR2020), Communications in Computer & Information Science (CCIS), Springer 2020.

4. Nalmpantis O. and Tjortjis C., 'The 50/50 Recommender: a Method Incorporating Personality into Movie Recommender Systems', CCIS 'Communications in Computer and Information Science, pp. 498-507, 2017, Springer-Verlag, ISBN 978-3-319-65171-2.

5.   Yakhchi S., Ghafari S.M., Tjortjis C., Fazeli M., 'ARMICA-Improved: A New Approach for Association Rule Mining', Lecture Notes in Artificial Indigence, vol 10412, pp. 296-306, 2017, Springer-Verlag, ISBN 978-3-319-63557-6.

6.   Arshad S., Tjortjis C. 'Clustering Software Metric Values Extracted from C# Code for Maintainability Assessment', Article No. 24, ACM Int'l Conf. Proc. Series, 2016, ACM, ISBN: 978-1-4503-3734-2.

7.   Papas D. and Tjortjis C., 'Combining Clustering and Classification for Software Quality Evaluation', LNCS 8445, pp. 273-286, 2014, Springer-Verlag, ISBN 978-3-319-07064-3. Scimago Q2.

8.   Karageorgos A., Avramouli D., Tjortjis C., Ntalos G., 'Agent-based Digital Networking in Furniture Manufacturing Enterprises', in Communications in Computer and Information Science (CCIS) LNCS, 2010, Springer-Verlag, ISBN 978-3-642-14305-2.

9.   Muyeba M., Khan M., Malik, Z. and Tjortjis C., 'Towards Healthy Association Rule Mining (HARM): A Fuzzy Quantitative Approach', in Lecture Notes Computer Science, Vol. 4224, pp.1014-1022, 2006, ISSN: 0302-9743. Scimago Q2.

10.   Wang C., and Tjortjis C., 'PRICES: An Efficient Algorithm for Mining Association Rules' in Lecture Notes Computer Science Vol. 3177, pp. 352-358, 2004, Springer-Verlag, ISSN: 0302-9743. Scimago Q2.

11.   Dong L. and Tjortjis C., 'Experiences of Using a Quantitative Approach for Mining Association Rules' in Lecture Notes Computer Science Vol. 2690, pp. 693-700, 2003, Springer-Verlag, ISSN: 0302-9743. Scimago Q2.

12.   Tjortjis C. and Keane J.A., 'T3: an Improved Classification Algorithm for Data Mining' in Lecture Notes Computer Science Vol. 2412, pp. 50-55, 2002, Springer-Verlag, ISSN: 0302-9743. Scimago Q2. Executable version of T3.

 

Publications in refereed Int'l Conferences   

13. D. Karapiperis, C. Tjortjis, V.S. Verykios, “A Randomized Blocking Structure for Streaming Record Linkage”, Proc. 49th Int’l Conf. on Very Large Data Bases (PVLDB 23), 16(11): 2783 - 2791, 2023.

14. M.M. Al Chawa, R. Tetzlaff, C. Tjortjis, S.G. Stavrinides, C. de Benito and R. Picos, “A Behavioural Compact Model for Programmable Neuromorphic ReRAM”, Proc. 18th ACM Int’l Symposium on Na-noscale Architectures (NANOARCH 2023), Article No.: 2, pp. 1-3, December 2023,

15. S. Stavrinides, P. Tzounakis, C. de Benito, C. Tjortjis, M.M. Al Chawa, I. Antoniou, and R. Picos, “Implementation of Reservoir Computers using Simulated Electrostatically Linked Systems”, Proc. 18th IEEE Int’l Workshop on Cellular Nanoscale Networks and their Applications (CNNA 23), 2023.

16. S.G. Stavrinides, L. Bush-Espinosa, C. de Benito, N.A. Anagnostopoulos, T. Arul, S. Katzenbeisser, C. Tjortjis, M.M. Al Chawa, R. Picos, “Exploiting Optical Nonlinear Temporal Coupling for Implementing Physical Unclonable Functions”, Proc. IEEE 9th World Forum on Internet of Things (WFIoT 23), 2023.

17. A. Mystakidis, N. Tsalikidis, P. Koukaras, C. Kontoulis, P.A. Gkaidatzis, D. Ioannidis, C. Tjortjis, and D. Tzovaras, “Power Load Forecasting: A Time-Series Multi-Step Ahead and Multi-Model Analysis”, Proc. IEEE 58th Int’l Universities Power Engineering Conference (UPEC 23), 2023.

18. C. Dontaki, P. Koukaras, and C. Tjortjis, “Sentiment Analysis on English and Greek Twitter Data regarding Vaccinations”, Proc. 14th Int’l Conf. on Information, Intelligence, Systems and Applications (IISA 23), 2023.

19. P. Anastasiou, K. Tzafilkou, D. Karapiperis, C. Tjortjis, “YouTube Sentiment Analysis on Healthcare Product Campaigns: Combining Lexicons and Machine Learning Models”, Proc. 14th Int’l Conf. on In-formation, Intelligence, Systems and Applications (IISA 23), 2023.

20. M. Vasileiou, G. Papageorgiou, C. Tjortjis, “A Machine Learning Approach for Effective Software Defect Detection”, Proc. 14th Int’l Conf. on Information, Intelligence, Systems and Applications (IISA 23), 2023 .

21. A. Mystakidis, O. Geromichalou, C. Tjortjis, “Data Mining for Smart Cities: Traffic Congestion Prediction”, Proc. 14th Int’l Conf. on Information, Intelligence, Systems and Applications (IISA 23), 2023 .

22. V. Chouliara, P. Koukaras and C. Tjortjis, “Fake News Detection utilizing textual cues”, Proc. 19th Int’l Conf. on Artificial Intelligence Applications and Innovations (AIAI 23).

23. N. Giannakoulas, G. Papageorgiou, C. Tjortjis, “Forecasting Goal Performance for Top League Football Players: A Comparative Study”, Proc. 19th Int’l Conf. on Artificial Intelligence Applications and Innova-tions (AIAI 23).

24. A. Mystakidis, E. Ntozi, K. Afentoulis, P. Koukaras, G. Giannopoulos, N. Bezas, P. Gkaidatzis, D. Ioannidis, C. Tjortjis and D. Tzovaras, “One Step Ahead Energy Load Forecasting: Multi-model approach utilizing Machine and Deep Learning”, Proc. IEEE 57th Int’l Universities Power Engineering Conference (UPEC 2022), 2022

25. Ε. Kapoteli, P. Koukaras, C. Tjortjis, Social Media Sentiment Analysis Related to COVID-19 Vaccines: Case studies in English and Greek language, Proc. 18th Int’l Conf. Artificial Intelligence Applications and Innovations (AIAI 22).

26. M. Karagkiozidou, P. Koukaras, C. Tjortjis, Sentiment Analysis on COVID-19 Twitter Data: A Sentiment Timeline, Proc. 18th Int’l Conf. Artificial Intelligence Applications and Innovations (AIAI 22).

27. P. Koukaras, A. Dimara, S. Herrera, N. Zangrando, S. Krinidis, D. Ioannidis, P. Fraternali, C. Tjortjis, C.-N. Anagnostopoulos, D. Tzovaras, Proactive buildings: A prescriptive maintenance approach, Proc. 18th Int’l Conf. Artificial Intelligence Applications and Innovations (AIAI 22).

28.. N. Zangrando, S. Herrera, P. Koukaras, A. Dimara, P. Fraternali, S. Krinidis, D. Ioannidis, C. Tjortjis, C.-N. Anagnostopoulos, D. Tzovaras, Anomaly detection in small-scale industrial and household appliances, Proc. 18th Int’l Conf. Artificial Intelligence Applications and Innovations (AIAI 22).

29. A. Ahmed, C. Tjortjis, “Machine Learning based IoT-BotNet Attack Detection Using Real-time Heterogeneous Data”, 2nd Int’l Conf. on Electrical, Computer and Energy Technologies (ICECET 22).

30. P. Koukaras, V. Tsichli, and C. Tjortjis, 'Predicting Stock Market Movements with Social Media and Machine Learning', Proc. 17th Int’l Conf. on Web Information Systems and Technologies (WEBIST 21), 2021

31. A. Avramidou and C. Tjortjis, 'Predicting CO2 Emissions for Buildings Using Regression and Classification', Proc. 17th IFIP Int’l Conf. on Artificial Intelligence Applications and Innovations (AIAI 21).

32. D. P. Kasseropoulos and C. Tjortjis, 'An Approach Utilizing Linguistic Features for Fake News Detection', Proc. 17th IFIP Int’l Conf. on Artificial Intelligence Applications and Innovations (AIAI 21)

33. C. Nousi and C. Tjortjis, 'A Methodology for Stock Movement Prediction Using Sentiment Analysis on Twitter and StockTwits Data', Proc. 6th IEEE South-East Europe Design Automation, Computer Engineering, Computer Networks and Social Media Conference (SEEDA-CECNSM 21), 2021.

34. A. Mystakidis, C. Tjortjis, 'Big Data Mining for Smart Cities: Predicting Traffic Congestion using Classification', Proc.11th IEEE Int’l Conf. on Information, Intelligence, Systems and Applications (IISA 20) 2020.

35. V. Chazan–Pantzalis, C. Tjortjis, ' Sports Analytics for Football League Table and Player Performance Prediction', Proc. 11th IEEE Int’l Conf. on Information, Intelligence, Systems and Applications (IISA 20) 2020.

36. D. Beleveslis, C. Tjortjis, 'Promoting Diversity in Content Based Recommendation using Feature Weighting and LSH', 16th Int'l Conf. on Artificial Intelligence Applications and Innovations (AIAI 20) 2020.

37.     K. Christantonis, C. Tjortjis, A. Manos, D.E. Filippidou, Ε. Mougiakou and E. Christelis, 'Using Classification for Traffic Prediction in Smart Cities', 16th Int'l Conf. on Artificial Intelligence Applications and Innovations (AIAI 20) 2020.

38.     E. Tsiara, C. Tjortjis, 'Using Twitter to Predict Chart Position for Songs', 16th Int'l Conf. on Artificial Intelligence Applications and Innovations (AIAI 20), 2020.

39.     Beleveslis D., Tjortjis C., Psaradelis D. and Nikoglou D., 'A Hybrid Method for Sentiment Analysis of Election Related Tweets', 4th IEEE SE Europe Design Automation, Computer Engineering, Computer Networks, and Social Media Conf. (SEEDA-CECNSM) 2019.

40.     Tasios D., Tjortjis C., Gregoriades A., 'Mining Traffic Accident Data for Hazard Causality Analysis', 4th IEEE SE Europe Design Automation, Computer Engineering, Computer Networks, and Social Media Conf. (SEEDA-CECNSM) 2019.

41.     Christantonis K., Tjortjis C., 'Data Mining for Smart Cities: Predicting Electricity Consumption by Classification', IEEE 10th Int'l Conf. on Information, Intelligence, Systems and Applications (IISA 2019), pp. 67-73, 2019.

42.     Apostolou K., Tjortjis C., 'Sports Analytics algorithms for performance prediction', IEEE 10th Int'l Conf. on Information, Intelligence, Systems and Applications (IISA 2019), pp. 469-472, 2019.

43.     Ι. Schoinas, C. Tjortjis, 'MuSIF: A Product Recommendation System Based on Multi-source Implicit Feedback', Proc. 15th Int'l Conf. on Artificial Intelligence Applications and Innovations (AIAI 19), IFIP AICT 559, pp. 660-672, Springer, 2019.

44.     L. Oikonomou and C. Tjortjis, 'A Method for Predicting the Winner of the USA Presidential Elections using Data Extracted from Twitter', 3rd IEEE SE Europe Design Automation, Computer Engineering, Computer Networks, and Social Media Conf. (IEEE SEEDA-CECNSM18), 2018.

45.    Theodorou T.I., Salamanis A., Kehagias D., Tzovaras D., and Tjortjis C., 'Short-Term Traffic Prediction Under both Typical and Atypical Traffic Conditions using a Pattern Transition Model', 3rd Int'l Conf. Vehicle Technology and Intelligent Transport Systems (VEHITS 17), pp. 79-89, 2017.

46.    Ghafari S.M. and Tjortjis C., 'Association Rules Mining by improving the Imperialism Competitive Algorithm (ARMICA) ', IFIP AICT Proc. 12th Int'l Conf. on Artificial Intelligence Applications and Innovations (AIAI 2016). Vol. 475, pp 242-254, Springer, 2016.

47.    Gerogiannis V.C., Karageorgos A., Liu L., and Tjortjis C., 'Personalised Fuzzy Recommendation for High Involvement Products', IEEE Int'l Conf. Systems, Man, and Cybernetics (SMC 2013), pp. 4884-4890, 2013.

48.    Karageorgos A., Avramouli D., Vasilopoulou K., Tjortjis C., Ntalos G., 'Towards Agent-based Smart Collaboration in Enterprise Networks', in 8th  Int'l Workshop on Agent-based Computing for Enterprise Collaboration (ACEC) at WETICE 2010, pp. 35-40, 2010.

49.    Singer J., Tjortjis C. and Ward M., 'Using Software Metrics to Evaluate Static Single Assignment Form in GCC', in Proc. 2nd Int'l Workshop on GCC Research Opportunities (GROW'10), pp. 73-88, 2010.

50.    Tjortjis C., and Visser J., '3rd International Workshop on Software Quality and Maintainability', Proc. IEEE 13th European Conf. Software Maintenance and Reengineering (CSMR 2009), IEEE Comp. Soc. Press, pp. 271-272, 2009.

51.    Antonellis P., Antoniou D., Kanellopoulos Y., Makris C., Theodoridis E., Tjortjis C., Tsirakis N., 'Code4Thought Project: Employing the ISO/IEC-9126 standard for Software Engineering - Product Quality Assessment', at the 13th European Conf. Software Maintenance and Reengineering (CSMR 09), pp. 297-300, 2009.

52.    Antonellis P., Antoniou D.,  Kanellopoulos Y., Makris C., Theodoridis E., Tjortjis C., Tsirakis N., 'Employing Clustering for Assisting Source Code Maintainability Evaluation according to ISO/IEC-9126', at the Artificial Intelligence Techniques in Software Engineering Workshop (AISEW 2008) in ECAI08.

53.    Kanellopoulos Y., Heitlager I., Tjortjis C., and Visser J., 'Interpretation of Source Code Clusters in Terms of ISO/IEC-9126 Quality Aspects', at the 12th European Conf. Software Maintenance and Reengineering (CSMR 08), pp. 63-72, 2008..

54.    Antonellis P., Antoniou D., Kanellopoulos Y., Makris C., Theodoridis E., Tjortjis C., Tsirakis N., 'Monitoring the Evolution of Software Systems Maintainability', Proc. special sessions in IEEE 12th European Conference on Software Maintenance and Reengineering (CSMR 2008), 2008.

55.    Kanellopoulos Y., Antonellis P., Tjortjis C. and Makris C., 'k-Attractors: A Clustering Algorithm for Software Measurement Data Analysis', Proc. 19th IEEE Int'l Conf. on Tools with Artificial Intelligence, (ICTAI 07), pp.358-365, 2007.

56.    Tjortjis C., and Wang C., 'HybridSet: An Effective Approach to Association Rule Mining', Proc. 22nd European Conf. on Operational Research EURO XXII, 2007.

57   Antonellis P., Antoniou D., Kanellopoulos Y., Makris C., Theodoridis E., Tjortjis C., Tsirakis N., 'A Data Mining Methodology for Evaluating Maintainability according to ISO/IEC-9126 Software Engineering-Product Quality Standard', Proc. special sessions in IEEE 11th European Conf. on Software Maintenance and Reengineering (CSMR 2007), pp. 81-89, 2007.

58.    Khan M.S., Muyeba M., Tjortjis C., and F. Coenen, 'An Effective Fuzzy Healthy Association Rule Mining Algorithm (FHARM)',  at the 7th Annual Workshop on Computational Intelligence (UKCI 2007).

59.    Denaxas S. and Tjortjis C., 'Quantifying the Biological Similarity between Gene Products Using GO: An Application of the Vector Space Model', at the IEEE Information Technology in Biomedicine (ITAB 2006).

60.    Marchant J., Tjortjis C., and Turega M., 'A Metric of Confidence in Requirements Gathered from Legacy Systems: Two Industrial Case Studies' at the IEEE 10th European Conf. Software Maintenance and Reengineering (CSMR 2006), pp. 353-359, 2006.

61.    Rousidis D. and Tjortjis C., 'Clustering data retrieved from Java source code to support software maintenance: A case study', at the IEEE 9th European Conf. Software Maintenance and Reengineering (CSMR 2005), pp. 276-279, 2005.

62.    Denaxas S. and Tjortjis C., 'Building a multi-level database for efficient information retrieval: A framework definition', at the IASTED Int'l Conf. on Software Engineering (SE 2005), pp. 163-170, 2005.

63.    Kanellopoulos Y. and Tjortjis C., 'Data Mining Source Code to Facilitate Program Comprehension: Experiments on Clustering Data Retrieved from C++ Programs', at the IEEE 12th Int'l Workshop on Program Comprehension (IWPC 2004), pp. 214-223, 2004.

64.    Wang C., and Tjortjis C., 'A New Fast Algorithm for Mining Association Rules Using Logical Operations' at Proc. EPSRC/IEEE/IEE PG Research Conf.  (PREP 2004), pp. 33-34, 2004..

65.    Tjortjis C., Sinos L. and Layzell P.J., 'Facilitating Program Comprehension by Mining Association Rules from Source Code', at the IEEE 11th Int'l Workshop Program Comprehension (IWPC 03), pp. 125-132, 2003.

66.    Tjortjis C., Gold N., Layzell P.J. and Bennett K., 'From System Comprehension to Program Comprehension' at the IEEE 26th Int'l Computer Software Applications Conf. (COMPSAC 02), pp. 427-432, 2002.

67.    Tjortjis C., Dafoulas G., Layzell P.J., Macaulay L., 'A Model for Selecting CSCW Technologies for Distributed Software Maintenance Teams in Virtual Organisations' at the IEEE 26th Int'l Computer Software Applications Conf. (COMPSAC 02), pp. 1104-1108, 2002.

68.    Chen K., Tjortjis C. and Layzell P.J., 'A Method for Legacy Systems Maintenance by Mining Data Extracted from Source Code' at the IEEE 6th European Conf. on Software Maintenance and Reengineering (CSMR 2002), pp. 54-60. 2002.

69.    Tjortjis C. and Layzell P.J., 'Using Data Mining to Assess Software Reliability' at the IEEE 12th Int'l Symposium on Software Reliability Engineering (ISSRE2001), pp. 221-223, 2001.

70.    Tjortjis C. and Layzell P.J., 'Expert Maintainers' Strategies and Needs when Understanding Software: A Qualitative Empirical Study' at the IEEE 8th Asia-Pacific Software Engineering Conf. (APSEC 2001),pp. 281-287, 2001.

71.    Karanikas H., Tjortjis C., Theodoulidis B., 'An approach to Text mining using Information Extraction' at the Proc. PKDD 2000 Workshop on Knowledge Management Theory & Applications (KMTA2000), pp.165-178, 2000.

72.    Scott R.I, Svinterikou S., Tjortjis C. and Keane J.A, 'Experiences of using Data Mining in a Banking Application' at the 2nd WSES/IEEE/IMCS Int'l Conf. on: Circuits, Systems and Computers (CSC'98), pp. 343-346, 1998.

 

Publications in refereed National Conferences

1.      Rousidis D. and Tjortjis C., 'Understanding Java Source Code by Using Data Mining Clustering', at Proc. 10th Pan'c Conf. on Informatics (PCI'2005), 2005.

2.      Denaxas S. and Tjortjis C., 'A Hybrid Knowledge-Driver Approach to Clustering Gene Expression Data', at Proc. 10th Pan'c Conf. on Informatics (PCI'2005), 2005.

3.      Gioldasis G., Panagopoulou G. Sirmakesis S., Tjortjis C., Tsakalidis A., 'A Complete Model of an Information System for Hospitals', at Proc. 3rd Nat'l Conf. of Medical Informatics, 1994.

 

 

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