George Paliouras is a Researcher at the IIT in the NCSR Demokritos in Athens, Greece.
He is heading the Division of Intelligent Information Systems of IIT.
He is also adjunct professor at the Department of Computer Science, University of Huston, USA.
Scholar Profile | CV in English | Contact
Home
Publications
  Books / Sp. issues
Theses
Journals
Book chapters
Conferences
Reports
Patents
Press
Projects
  International
National
Commercial
Software
Services
Talks
  International
National
Research associates
  Current associates
Past associates
Community activities
  Societes
Journals
Conferences
Research Interests

machine learning, knowledge discovery, artificial intelligence, personalization, user modelling, information filtering, information extraction, event recognition, ontology learning, grammar learning, Web mining

Current and Recent Activities

The second BioASQ challenge is starting soon. Check the Call for Participation!.
Will be giving an invited talk about BioASQ at BioTxtM in LREC 2014.
BioASQ has joined forces with other teams to co-organise the CLEF 2014 QA Track.
Coordinating the project SPEEDD (Scalable ProactivE Event-Driven Decision making).
Coordinating the project BioASQ (A challenge on large-scale biomedical semantic indexing and question answering).
Participating in the project REVEAL (REVEALing hidden concepts in Social Media).
Co-organising the 4th Large Scale Hierarchical Text Classification challenge.
Check our generic and free personalization server PServer, provided in cooperation with Scify.
Check gov.insight, an open text analytics service for public consultations (in Greek).
Undergrad and postgrad theses by the division of Intelligent Information Systems (in Greek).
Serving in the editorial board of COIN.

Ten Selected Recent Publications
  1. A. Skarlatidis, A. Artikis, J. Filippou and G. Paliouras, "A Probabilistic Logic Programming Event Calculus," Theory and Practice of Logic Programming, 2014, to appear. (pdf preprint)

  2. A. Krithara and G. Paliouras, "TL-PLSA: Transfer learning between domains with different classes," Proceedings of the IEEE International Conference on Data Mining (ICDM), Dallas, Texas, USA, December 7-10, 2013. (pdf)

  3. A. Artikis, A. Skarlatidis, F. Portet and G. Paliouras, "Logic-Based Event Recognition," The Knowledge Engineering Review, v. 27, n. 4, pp. 469-506, 2012. (KER online version) (pdf preprint)

  4. G. Paliouras, "Discovery of Web user communities and their role in personalization," Special Issue on Coming of Age: Celebrating a Quarter Century of User Modeling and Personalization, J. Kay and G. McCalla (editors), User Modeling and User-Adapted Interaction, v. 22, n. 1-2, pp. 151-175, 2012. (UMUAI online version) (pdf preprint)

  5. A. Artikis, M. Sergot and G. Paliouras, "Run-time composite event recognition," Proceedings of the 6th ACM International Conference on Distributed Event-Based Systems (DEBS), pp. 69-80, 2012. (ACM online version) (pdf)

  6. E. Zavitsanos, G. Paliouras and G. Vouros, "Non-Parametric Estimation of Topic Hierarchies from Texts with Hierarchical Dirichlet Processes," Journal of Machine Learning Research, v. 12, pp. 2749-2775, 2011. (JMLR online version) (pdf)

  7. E. Zavitsanos, G. Paliouras and G. Vouros, "Gold Standard Evaluation of Ontology Learning Methods Through Ontology Transformation and Alignment," IEEE Transactions on Knowledge and Data Engineering, v. 23, n. 11, pp. 1635-1648, 2011. (IEEE online version) (pdf preprint)

  8. G. Paliouras, C.D. Spyropoulos and G. Tsatsaronis (editors), Knowledge-Driven Multimedia Information Extraction and Ontology Evolution - Bridging the Semantic Gap. Lecture Notes in Artificial Intelligence, n. 6050, Springer-Verlag, 2011. (online version)

  9. A. Skarlatidis, G. Paliouras, G. Vouros and A. Artikis, "Probabilistic Event Calculus based on Markov Logic Networks," Proceedings of the 5th International Symposium on Rules: Research Based and Industry Focused (RuleML), pp. 155-170, 2011. (Springer online version) (pdf)

  10. D. Pierrakos, G. Paliouras, "Personalizing Web Directories with the aid of Web Usage Data," IEEE Transactions on Knowledge and Data Engineering, v. 22, n. 9, pp. 1331-1344, 2010. (abstract) (IEEE online version) (pdf preprint)