Dr Christos Berberidis

Christos Berberidis received his PhD from the Department of Informatics of Aristotle University of Thessaloniki. He holds a BSc. from the Department of Informatics of Aristotle University (1998) and an MSc. in Information Systems Engineering from University of Manchester, UK (1999) (UMIST).

His research has been focused on Data Mining and Machine Learning, mostly on temporal and sequential data. He is also working on data mining in biological data, for the prediction of functional sites in genomic sequences. He is the author of several papers in scientific journals and conference proceedings.

Christos has worked as a visiting researcher at the Department of Computer Sciences of Purdue University (IN, USA). For the past 2 years he has been working as an Adjunct Lecturer at the Department of Informatics, of Aristotle University, teaching basic and advanced programming techniques. He has participated in many R&D projects and has also significant experience as a research consultant and project manager in the private sector.

List of Publications


  1. E. Kontopoulos, C. Berberidis, T. Dergiades, N. Bassiliades, “Ontology-based Sentiment Analysis of Twitter Posts”, Expert Systems with Applications, (in press, available online January 2013)
  2. C. Berberidis, I. Vlahavas, “Mining for weak periodic signals in time series databases”, Journal of Intelligent Data Analysis, Volume 9(1), IOS Press, 2005
  3. C. Berberidis and I. Vlahavas, “Detection And Prediction Of Rare Events In Transaction Databases”, International Journal of Artificial Intelligence Tools (IJAIT), World Scientific, 16(5), pp. 829 – 848, 2007
  4. G. Tzanis and C. Berberidis, “Mining for Mutually Exclusive Items in Transaction Databases”, International Journal of Data Warehousing and Mining, David Taniar (Ed.), Idea Group Publishing, 3(3), 2007
  5. Tzanis G., Berberidis C. and Vlahavas P. I., “StackTIS: A Stacked Generalization Approach for Effective Prediction of Translation Initiation Sites”, Computers in Biology and Medicine, Elsevier, November 2011

Book chapters

  1. G. Tzanis, C. Berberidis, I. Vlahavas, “Machine Learning and Data Mining in Bioinformatics”, Handbook of Research on Innovations in Database Technologies and Applications: Current and Future Trends, Viviana E. Ferraggine, Jorge H. Doorn, and Laura C. Rivero (Eds.), IDEA Group Publishing, 978-1-60566-242-8, February 2009.


  1. C. Berberidis, A. G. Walid, M. Atallah, I. Vlahavas and A. K. Elmagarmid, “Multiple and Partial Periodicity Mining in Time Series Databases”, Proc. 15th European Conference on Artificial Intelligence (ECAI 2002), pp. 370-374, Lyon, France, 2002, IOS Press, pp.370-374
  2. C. Berberidis, I. Vlahavas, W. G. Aref, M. Atallah and A. K. Elmagarmid, “On the Discovery of Weak Periodicities in Large Time Series”, Proc. 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD’02), Helsinki, Finland, August 2002, Springer-Verlag, LNAI, vol. 2431, pp.51-61
  3. C. Berberidis, I. Vlahavas, “Periodicity Mining in Industrial Data: A Real World Example on Power Data”, Proc. First International Conference for Mathematics and Informatics for Industry (MII 2003), Thessaloniki, Greece, April 14-16 2003
  4. C. Berberidis, L, Angelis, I. Vlahavas, “Inter-transaction Association Rules Mining for Rare Events Prediction”, In Proc. (companion
    volume) 3rd Hellenic Conference on Artificial Intelligence (SETN ’04), Samos, Greece, 2004
  5. C. Berberidis, L, Angelis, I. Vlahavas, “PREVENT: An algorithm for mining inter-transactional patterns for the prediction of rare events”, Proc. 2nd European Starting AI Researcher Symposium (STAIRS’ 04), IOS Press, Valencia, Spain, 23-24 August 2004
  6. C. Berberidis, G. Tzanis, “Mining for Contiguous Frequent Itemsets in Transaction Databases”, IEEE Third International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS’2005), Sofia, Bulgaria, September 5-7, 2005
  7. G. Tzanis, C. Berberidis, A. Alexandridou, I. Vlahavas, “Improving the Accuracy of Classifiers for the Prediction of Translation Initiation Sites in Genomic Sequences”, In Proc. 10th Panhellenic Conference on Informatics (PCI’2005), P. Bozanis and E.N. Houstis (Eds.), Springer-Verlag, LNCS 3746, pp. 426-436, Volos, Greece, 11-13 November 2005
  8. G. Tzanis, C. Berberidis, and I. Vlahavas, “On the Discovery of Mutually Exclusive Items in a Market Basket Database”, In Proc. 2nd ADBIS Workshop on Data Mining and Knowledge Discovery (ADMKD 2006), Thessaloniki, Greece, September 6, 2006
  9. G. Tzanis, C. Berberidis and I. Vlahavas, “A Novel Data Mining Approach for the Accurate Prediction of Translation Initiation Sites”, In Proc. 7th International Symposium on Biological and Medical Data Analysis (ISBMDA 2006), Springer LNCS, Thessaloniki, Greece, December 7-8, 2006
  10. G. Tzanis, C. Berberidis, I. Vlahavas, “MANTIS: A Data Mining Methodology for Effective Translation Initiation Site Prediction”, Proceedings of the 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, IEEE, Lyon, France, 2007.


  1. G. Tzanis, C. Berberidis, I. Vlahavas, “Biological Data Mining” Encyclopedia of Database Technologies and Applications, Laura C. Rivero, Jorge H. Doorn and Viviana E. Ferraggine (Eds.), IDEA Group Publishing, April 2005.