Christos Tjortjis

Personal web page

Dr. Christos Tjortjis is an Associate Professor in Knowledge Discovery and Software Engineering systems and Programme Director for the MSc in Data Science, the MSc in ICT systems and the MSc in Smart Cities and Communities at the International Hellenic UniversitySchool of Science & Technology. He worked as a tenured lecturer for the University of Manchester, Schools of Computer Science and Informatics as well as for UMIST, Dept. of Computation. He also worked as adjunct assistant/associate professor at the University of Ioannina, Dept. of Computer Science, and adjunct lecturer/assistant professor at the University of Western Macedonia, Dept. Engineering Informatics and Telecommunications.

He received a PhD in Informatics from the University of Manchester, an MPhil in Computation from UMIST, a BSc in Law from the Demokritos University of Thrace and a Diploma of Engineering in Computer Engineering and Informatics from the University of Patras.

His focal research area is data mining and software engineering, and his aim is to advance the use of data mining in domains such as programming languages and novel types of heterogeneous data. His research interests are in the areas of data, code and text mining, and software maintenance and quality, where he has published widely. His research objectives include bridging the gap between theories and applications of data mining, accelerating and increasing the effectiveness of software maintenance and reducing its costs by improving quality and facilitating evolution as well as establishing novel ways of retrieving information from text and source code. He published some 60 papers in int’l journals and conferences. He was on the Program Committee of more than 80 and on the Organizational Committee of 9 conferences / workshops. He has been involved in several projects concerning data and text mining, data recovery, software quality and evolution etc., leading 7 of them.

Selected Publications

  1. Tjortjis C., ‘Mining Association Rules from Code (MARC) to Support Legacy Software Management’, Software Quality Journal. 2020 (Springer) • Journal Paper
  2. Rousidis D., Koukaras P., Tjortjis C., ‘Social Media Prediction A Literature Review’, Multimedia Tools and Applications, 79(9), 6279-6311, 2020 (Springer) • Journal Paper
  3. P. Koukaras, C. Tjortjis, D. Rousidis, “Social Media Types: Introducing a Data Driven Taxonomy”, Computing, Vol. 102, no. 1, pp. 295-340, 2020 (Springer) • Journal Paper
  4. S.M.Ghafari, C. Tjortjis, “A Survey on Association Rules Mining Using Heuristics”, WIREs Data Mining and Knowledge Discovery, 2019 (Wiley) • Journal Paper
  5. D. Beleveslis, C. Tjortjis, D. Psaradelis and D. Nikoglou, “A Hybrid Method for Sentiment Analysis of Election Related Tweets”, Proc. 4th IEEE SE Europe Design Automation, Computer Engineer-ing, Computer Networks, and Social Media Conf. (SEEDA-CECNSM), pp. 1-7, 2019 • Conference Paper
  6. D. Tasios, C. Tjortjis, A. Gregoriades, “Mining Traffic Accident Data for Hazard Causality Analysis” Proc. 4th IEEE SE Europe Design Automation, Computer Engineering, Computer Networks, and Social Media Conf. (SEEDA-CECNSM), pp. 1-7, 2019 (IEEE) • Conference Paper
  7. K. Christantonis, C. Tjortjis, “Data Mining for Smart Cities: Predicting Electricity Consumption by Classification”, Proc. 10th IEEE Int’l Conf. on Information, Intelligence, Systems and Applications (IISA 2019), pp. 67-73, 2019 (IEEE) • Conference Paper
  8. K. Apostolou, C. Tjortjis, “Sports Analytics algorithms for performance prediction”, 10th IEEE Int’l Conf. on Information, Intelligence, Systems and Applications, (IISA 2019), pp. 469-472, 2019 (IEEE) • Conference Paper
  9. Ι. Schoinas, C. Tjortjis, “MuSIF: A Product Recommendation System Based on Multi-source Implicit Feedback”, 15th Int’l Conf. on Artificial Intelligence Applications and Innovations (AIAI 19), IFIP AICT 559, pp. 1–13, 2019 (Springer) • Conference Paper
  10. P. Koukaras, D. Rousidis, C. Tjortjis, “Forecasting and Prevention mechanisms using Social Media in Healthcare”, Advanced Computational Intelligence Paradigms in Healthcare, 2020 (Springer) • Book chapter
  11. P. Koukaras, C. Tjortjis, “Social Media Analytics, types and methodology”, Machine Learning Paradigms: Applications of Learning and Analytics in Intelligent Systems, 2019 (Springer) • Book chapter
  12. M. Koubarakis, G. Vouros, G. Chalkiadakis, V. Plagianakos, C. Tjortjis, E. Kavallieratou, D. Vrakas, N. Mavridis, G. Petasis, K. Blekas, A. Krithara, “AI in Greece: The Case of Research on Linked Geospatial Data”, the AI magazine, Vol 39, No 2, pp. 91-96, 2018 (AAAI) • Journal Paper
  13. L. Oikonomou and C. Tjortjis, “A Method for Predicting the Winner of the USA Presidential Elections using Data Extracted from Twitter”, Proc. 3rd SEEDA Computer Engineering, Computer Networks, and Social Media Conference (CECNSM18), 2018 (IEEE) • Conference Paper
  14. 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) • Journal Paper
  15. S. Yakhchi, S.M. Ghafari, C. Tjortjis, M. Fazeli, “ARMICA-Improved: A New Approach for Association Rule Mining”, LNAI, vol 10412, pp. 296-306, 2017 (Springer-Verlag) • Conference Paper
  16. Nalmpantis O. and Tjortjis C., “The 50/55 Recommender: a Method Incorporating Personality into Movie Recommender Systems”, Proc. 8th Int’l Conf. on Engineering Applications of Neural Networks (EANN 17), (CCIS) 744, pp. 1–10, 2017 (Springer-Verlag) • Conference Paper
  17. 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”, Proc. 3rd Int’l Conf. Vehicle Technology and Intelligent Transport Systems (VEHITS 17), pp. 79-89, 2017 • Conference Paper
  18. Ghafari S.M. and Tjortjis C., “Association Rules Mining by improving the Imperialism Competitive Algorithm (ARMICA)”, AICT Proc. 12th Int’l Conf. on Artificial Intelligence Applications and Innovations (AIAI 2016). Springer, 2016 (IFIP) • Conference Paper
  19. Arshad S., Tjortjis C., “Clustering Software Metric Values Extracted from C# Code for Maintainability Assessment”, SETN 16, Article No. 24, Int’l Conf. Proc. Series, 2016 (ACM) • Conference Paper
  20. D. Papas and C. Tjortjis, “Combining Clustering and Classification for Software Quality Evaluation”, LNAI 8445, pp. 273–286, 2014 (Springer-Verlag) • Conference Paper
  21. V.A. Tatsis, C. Tjortjis, P. Tzirakis, “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) • Journal Paper
  22. V.C. Gerogiannis, A. Karageorgos, L. Liu, and C. Tjortjis, “Personalised Fuzzy Recommendation for High Involvement Products”, Int’l Conf. Systems, Man, and Cybernetics (SMC 2013), pp. 4884-4890, 2013 (IEEE) • Conference Paper
  23. 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) • Journal Paper
  24. Kanellopoulos Y., Antonellis P., Antoniou D., Makris C., Theodoridis E., Tjortjis C. and Tsirakis N., “Code Quality Evaluation methodology using the ISO/IEC 9126 Standard”, Int’l Journal of Software Engineering & Applications, Vol.1, No.3, pp. 17-36, 2010 (AIRCC) • Journal Paper
  25. A. Karageorgos, D. Avramouli, C. Tjortjis, G. Ntalos, “Agent-based Digital Networking in Furniture Manufacturing Enterprises”, Communications in Computer and Information Science (CCIS 88), pp. 381–395, 2010 (Springer-Verlag) • Conference Paper
  26. Antonellis P., Antoniou D., Kanellopoulos Y., Makris C., Theodoridis E., Tjortjis C. and Tsirakis N., “Clustering for Monitoring Software Systems Maintainability Evolution”, Electronic Notes in Theoretical Computer Science, Vol. 233, pp. 43-57, 2009 (Elsevier)• Journal Paper
  27. Antonellis P., Antoniou D., Kanellopoulos Y., Makris C., Theodoridis E., Tjortjis C. and Tsirakis N., “Code4Thought Project: Employing the ISO/IEC-9126 standard for Software Engineering – Product Quality Assessment”, Proc. 13th European Conf. Software Maintenance and Reengineering (CSMR 2009), pp. 297-300, 2009 (IEEE) • Conference Paper
  28. 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,) • Journal Paper
  29. 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) • Journal Paper
  30. 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) • Journal Paper
  31. Kanellopoulos Y., Heitlager I., Tjortjis C., and Visser J., “Interpretation of Source Code Clusters in Terms of the ISO/IEC-9126 Maintainability Characteristics”, Proc. 12th European Conf. Software Maintenance and Reengineering (CSMR 2008), pp. 63-72, 2008 (IEEE) • Conference Paper
  32. Kanellopoulos Y., Antonellis P., Tjortjis C. and Makris C., “k-Attractors: A Clustering Algorithm for Software Measurement Data Analysis”, Proc. 19th Int’l Conf. on Tools with Artificial Intelligence (ICTAI 07), pp. 358-365, 2007 (IEEE) • Conference Paper
  33. 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) • Journal Paper
  34. Tjortjis C. and Wang C., “HybridSet: An Effective Approach to Association Rule Mining”, Proc. 2007 European Conference on Operational Research (EURO XXII) (2007) • Conference Paper
  35. Tjortjis C., Saraee M., Theodoulidis B. and 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 (Schattauer GmbH) • Journal Paper
  36. Denaxas S. and Tjortjis C., “Quantifying the Biological Similarity between Gene Products Using GO: An Application of the Vector Space Model”, Proc. Information Technology in Biomedicine (ITAB 2006), 2006 (IEEE) • Conference Paper
  37. Kanellopoulos Y., Dimopoulos T., Tjortjis C. and Makris C., “Mining Source Code Elements for Comprehending Object-Oriented Systems and Evaluating Their Maintainability”, SIGKDD Explorations, Vol. 8, No. 1, pp. 33-40, 2006 (ACM Press) • Journal Paper
  38. Marchant J., Tjortjis C., and Turega M., “A Metric of Confidence in Requirements Gathered from Legacy Systems: Two Industrial Case Studies”, Proc. 10th European Conf. Software Maintenance and Reengineering (CSMR 2006), pp. 353-359, 2006 (IEEE) • Conference Paper
  39. Muyeba M., Khan M., Malik, Z. and Tjortjis C., “Towards Healthy Association Rule Mining (HARM): A Fuzzy Quantitative Approach”, LNCS , Vol. 4224, pp. 1014-1022, 2006 (Springer-Verlag) • Conference Paper
  40. Rousidis D. and Tjortjis C., “Clustering data retrieved from Java source code to support software maintenance: A case study”, Proc. 9th European Conf. Software Maintenance and Reengineering (CSMR 2005), pp. 276-279, 2005 (IEEE) • Conference Paper
  41. Kanellopoulos Y. and Tjortjis C., “Data Mining Source Code to Facilitate Program Comprehension: Experiments on Clustering Data Retrieved from C++ Programs”, Proc. 12th Int’l Workshop Program Comprehension (IWPC 2004), pp. 214-223, 2004 (IEEE) • Conference Paper
  42. Wang C. and Tjortjis C., “PRICES: An Efficient Algorithm for Mining Association Rules”, Lecture Notes in Computer Science, Vol. 3177, pp. 352-358, 2004 (Springer-Verlag,) • Conference Paper
  43. Dong L. and Tjortjis C., “Experiences of Using a Quantitative Approach for Mining Association Rules”, LNCS, Vol. 2690, pp. 693-700, 2003 (Springer-Verlag,) • Conference Paper
  44. Tjortjis C., Sinos L. and Layzell P.J., “Facilitating Program Comprehension by Mining Association Rules from Source Code”, Proc. 11th Int’l Workshop Program Comprehension (IWPC 03), pp. 125-132, 2003 (IEEE) • Conference Paper
  45. Tjortjis C. and Keane J.A, “T3: an Improved Classification Algorithm for Data Mining”, LNCS, Vol. 2412, pp. 50-55, 2002 (Springer-Verlag,) • Conference Paper
  46. Tjortjis C., Dafoulas G., Layzell P.J., Macaulay L. , “A Model for Selecting CSCW Technologies for Distributed Software Maintenance Teams in Virtual Organisations”, Proc. 26th Int’l Computer Software Applications Conf. (COMPSAC 02), pp. 1104-1108, 2002 (IEEE) • Conference Paper
  47. Tjortjis C., Gold N., Layzell P.J. and Bennett K., “From System Comprehension to Program Comprehension”, Proc. 26th Int’l Computer Software Applications Conf. (COMPSAC 02), pp. 427-432, 2002 (IEEE) • Conference Paper
  48. Tjortjis C. and Layzell P.J., “Expert Maintainers’ Strategies and Needs when Understanding Software: A Qualitative Empirical Study”, Proc. 8th Asia-Pacific Software Engineering Conf (APSEC 2001), pp. 281-287, 2001 (IEEE) • Conference Paper