Publications

Total Articles: 145

2016
	E. Spyromitros-Xioufis, G. Tsoumakas, W. Groves, I. Vlahavas, “Multi-Target Regression via Input Space Expansion: Treating Targets as Inputs”, Machine Learning, Johannes Fürnkranz (Ed.), Springer, 2016.
	Year Total: 1
2015
	N. Bassiliades, P. Fodor, A. Giurca, G. Gottlob, T. Kliegr, G. Nalepa, M. Palmirani, A. Paschke, M. Proctor, D. Roman, F. Sadri, N. Stojanovic, “Joint Proceedings of the 9th International Rule Challenge, the Special Track on Rule-based Recommender Systems for the Web of Data, RuleML2015 Industry Track and the 5th RuleML Doctoral Consortium”, CEUR Workshop Proceedings, ISSN 1613-0073, CEUR.org, 1417, Berlin, Germany, August 2-5, 2015, 2015.
	N. Bassiliades, G. Gottlob, F. Sadri, A. Paschke, D. Roman, “Rule Technologies: Foundations, Tools, and Applications, Proceedings of 9th International Symposium, RuleML 2015”, Lecture Notes in Computer Science, Springer, 9202, pp. 474, Berlin, Germany, August 2-5, 2015, 2015.
	N. Bassiliades, M. Ivanovic, M. Kon-Popovska, Y. Manolopoulos, T. Palpanas, G. Trajcevski, A. Vakali, “New Trends in Database and Information Systems II”, Selected papers of the 18th East European Conference on Advances in Databases and Information Systems and Associated Satellite Events, ADBIS 2014, Proceedings II, Springer, Advances in Intelligent Systems and Computing, Vol. 312, pp. 340, Ohrid, Macedonia, September 7-10, 2014, 2015.
	E. Papagiannopoulou, G. Tsoumakas, N. Bassiliades, “On Discovering Relationships in Multi-Label Learning via Linked Open Data”, 4th Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data (Know@LOD 2015), Johanna Völker, Heiko Paulheim, Jens Lehmann, Vojtech Svatek (Ed.), CEUR Workshop Proceedings, Vol-1365, 2015.
	R. Akerkar, V. Ermolayev, N. Bassiliades, “Editorial of Special issue on Web Intelligence, Mining and Semantics”, International Journal on Artificial Intelligence Tools, World Scientific, 24 (2), pp. 1502002, 2015.
	E. Spyromitros-Xioufis, S. Papadopoulos, A. Ginsca, A. Popescu, I. Kompatsiaris, I. Vlahavas, “Improving Diversity in Image Search via Supervised Relevance Scoring”, International Conference on Multimedia Retrieval, ACM, Shanghai, China, 2015.
	F. Markatopoulou, G. Tsoumakas, I. Vlahavas, “Dynamic Ensemble Pruning based on Multi-Label Classification”, Neurocomputing, Elsevier, Volume 150, Part B, pp. 501-512, 2015.
	Year Total: 7
2014
	I. Kavakiotis, A. Xochelli, A. Agathangelidis, G. Tsoumakas, N. Maglaveras, K. Stamatopoulos, A. Hadzidimitriou, I. Vlahavas, I. Chouvarda, “Integrating Multiple Immunogenetic Data Sources For Feature Extraction and Mining Mutation Patterns: The Case of Chronic Lymphocytic Leukemia Shared Mutations”, Statistical Methods for Omics Data Integration and Analysis. Heraklion, Crete, Greece, November 10-12, 2014.
	E. Spyromitros-Xioufis, S. Papadopoulos, I. Kompatsiaris, I. Vlahavas, “SocialSensor: Finding Diverse Images at MediaEval 2014”, CEUR Workshop Proceedings, CEUR-WS.org, Vol-1263, pp. 2, Barcelona, Catalunya, Spain, 2014.
	N. Spolaor, M. Monard, G. Tsoumakas, H. Lee, “Label Construction for Multi-label Feature Selection”, Proceedings of the 2014 Brazilian Conference on Intelligent Systems (BRACIS), São Carlos, Brazil, 2014.
	G. Tsoumakas, E. Spyromitros-Xioufis, I. Vlahavas, “Drawing Parallels between Multi-Label Classification and Multi-Target Regression”, ECML PKDD 2014 Workshop on Multi-Target Prediction, Nancy, France, 2014.
	I. Papanikolaou, D. Dimitriadis, G. Tsoumakas, M. Laliotis, N. Markantonatos, I. Vlahavas, “Ensemble Approaches for Large-Scale Multi-Label Classification and Question Answering in Biomedicine”, Proceedings BioASQ 2014 Workshop, Sheffield, UK, 2014.
	G. Tsoumakas, E. Spyromitros-Xioufis, A. Vrekou, I. Vlahavas, “Multi-Target Regression via Random Linear Target Combinations”, Proceedings of ECML PKDD 2014, Springer, Nancy, France, 2014.
	A. Arvanitidis, A. Serafi, A. Vakali, G. Tsoumakas, “Branty: A Social Media Ranking Tool For Brands”, Proceedings of ECML PKDD 2014, Springer, Nancy, France, 2014.
	R. Akerkar, N. Bassiliades, J. Davies, V. Ermolayev, “Research and Applications in Web Intelligence, Mining, and Semantics”, Proc. 4th International Conference on Web Intelligence, Mining and Semantics (WIMS’14), ACM, New York, NY, USA, DOI=10.1145/2611040.2611045, pp. Article 0, Thessaloniki, Greece, June 2-4 2014, 2014.
	R. Akerkar, N. Bassiliades, J. Davies, V. Ermolayev, “Proceedings of the 4th International Conference on Web Intelligence, Mining and Semantics (WIMS14)”, The ACM International Conference Proceedings Series, ACM, New York, USA, ISBN: 978-1-4503-2538-7, 2-4 June 2014, Thessaloniki, Greece, 2014.
	E. Spyromitros-Xioufis, S. Papadopoulos, I. Kompatsiaris, G. Tsoumakas, I. Vlahavas, “A Comprehensive Study over VLAD and Product Quantization in Large-scale Image Retrieval”, IEEE Transactions on Multimedia, IEEE, 2014.
	I. Kavakiotis, A. Triantafyllidis, G. Tsoumakas, I. Vlahavas, “Feature Evaluation Metrics for Population Genomic Data”, Proceedings of 8th Hellenic Conference on Artificial Intelligence (SETN 2014)., A. Likas, K. Blekas and D. Kalles (Eds.), Springer, Artificial intelligence: Methods and Applications, LNCS, 8445, pp. 436-441, Ioannina, Greece, May 15-17, 2014, 2014.
	A. Fachantidis, I. Partalas, M. Taylor, I. Vlahavas, “An Autonomous Transfer Learning Algorithm for TD-Learners”, Proc. 8th Hellenic Conference on Artificial Intelligence (SETN 2014), (in press), Ioannina, Greece, 2014.
	Y. Zhan, A. Fachantidis, I. Vlahavas, M. Taylor, “Agents Teaching Humans in Reinforcement Learning Tasks”, Adaptive Learning Agents 2014, (in press), Paris, France, 2014.
	P. Bailis, A. Fachantidis, I. Vlahavas, “Learning to play Monopoly: A Reinforcement Learning approach”, AISB 2014: AI & GAMES, (in press), London, U.K., 2014.
	M. Taylor, N. Charboni, A. Fachantidis, I. Vlahavas, L. Torrey, “Reinforcement Learning Agents Providing Advice in Complex Video Games”, Connection Science, Taylor & Francis, (in press), 2014.
	I. Kavakiotis, G. Tzanis, I. Vlahavas, “Polyadenylation site prediction using PolyA-iEP method”, Polyadenylation Method and Protocols, Joanna Rorbach and Agnieszka Bobrowicz (Eds.), Springer, Methods In Molecular Biology, 1125, pp. 131-140, 2014.
	I. Kavakiotis, A. Triantafyllidis, P. Samaras, A. Voulgaridis, N. Karaiskou, E. Konstantinidis, I. Vlahavas, “Pattern discovery for microsatellite genome analysis”, Computers in Biology and Medicine, Edward John Ciaccio (Ed.), Elsevier, 2014.
	I. Kavakiotis, G. Tzanis, I. Vlahavas, “Mining Frequent Patterns and Association Rules from Biological Data”, Biological Knowledge Discovery Handbook: Preprocessing, Mining and Postprocessing of Biological Data, Mourad Elloumi and Albert Y. Zomaya (Eds.), Wiley-Blackwell (John Wiley & Sons), 2014.
	Year Total: 18
2013
	A. Fachantidis, I. Partalas, M. Taylor, I. Vlahavas, “Autonomous Selection of Inter-Task Mappings in Transfer Learning”, 2013 AAAI Spring Symposium Series, AAAI, Stanford, U.S.A., 2013.
	A. Fachantidis, A. Di Nuovo, A. Cangelosi, I. Vlahavas, “Model-based reinforcement learning for humanoids: A study on forming rewards with the iCub platform”, Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB), 2013 IEEE SSCI, IEEE, pp. 87-93, Singapore, 2013.
	F. Briggs, Yonghong Huang, R. Raich, K. Eftaxias, Zhong Lei, W. Cukierski, S. Hadley, A. Hadley, M. Betts, X. Fern, J. Irvine, L. Neal, A. Thomas, G. Fodor, G. Tsoumakas, Hong Wei Ng, Thi Ngoc Tho Nguyen, H. Huttunen, P. Ruusuvuori, T. Manninen, A. Diment, T. Virtanen, J. Marzat, J. Defretin, D. Callender, C. Hurlburt, K. Larrey, M. Milakov, “The 9th annual MLSP competition: New methods for acoustic classification of multiple simultaneous bird species in a noisy environment”, Proc. 2013 IEEE International Workshop on Machine Learning for Signal Processing (MLSP), IEEE, 2013.
	N. Spolaor, G. Tsoumakas, “Evaluating Feature Selection Methods for Multi-Label Text Classification”, BioASQ Workshop, Valencia, Spain, September 27, 2013, 2013.
	G. Tsoumakas, M. Laliotis, N. Markantonatos, I. Vlahavas, “Large-Scale Semantic Indexing of Biomedical Publications at BioASQ”, BioASQ Workshop, Valencia, Spain, September 27, 2013, 2013.
	E. Kontopoulos, C. Berberidis, T. Dergiades, N. Bassiliades, “Ontology-based Sentiment Analysis of Twitter Posts”, Expert Systems with Applications, Elsevier, 40 (10), pp. 4065-4074, 2013.
	A. Fachantidis, I. Partalas, G. Tsoumakas, I. Vlahavas, “Transferring Task Models in Reinforcement Learning Agents”, Neurocomputing, Elsevier, 107, pp. 23-32, 2013.
	Year Total: 7
2012
	E. Spyromitros-Xioufis, S. Papadopoulos, I. Kompatsiaris, G. Tsoumakas, I. Vlahavas, “An empirical study on the combination of surf features with VLAD vectors for image search”, 13th International Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS), IEEE, 2012.
	G. Tzanis, C. Berberidis, I. Vlahavas, “StackTIS: A Stacked Generalization Approach for Effective Prediction of Translation Initiation Sites”, Computers in Biology and Medicine, Elsevier, Vol. 42, No. 1, pp. 61-69, 2012.
	A. Fachantidis, I. Partalas, M. Taylor, I. Vlahavas, “Transfer Learning via Multiple Inter-Task Mappings”, Recent Advances in Reinforcement Learning, Springer Berlin Heidelberg, pp. 225-236, 2012.
	K. Chatzidimitriou, I. Partalas, P. Mitkas, I. Vlahavas, “Transferring Evolved Reservoir Features in Reinforcement Learning Tasks”, Recent Advances in Reinforcement Learning, Lecture Notes in Computer Science, Springer-Verlag, 7188, pp. 213-224, 2012.
	Year Total: 4
2011
	K. Trohidis, G. Tsoumakas, G. Kalliris, I. Vlahavas, “Multi-label classification of music by emotion”, EURASIP Journal on Audio, Speech, and Music Processing, 2011:4, 2011.
	G. Boutsioukis, I. Partalas, I. Vlahavas, “Transfer Learning in Multi-agent Reinforcement Learning Domains”, Accepted for presentation at the 9th European Workshop on Reinforcement Learning and to be published in the Workshop Proceedings, 2011.
	E. Spyromitros-Xioufis, K. Sechidis, G. Tsoumakas, I. Vlahavas, “MLKD's Participation at the CLEF 2011 Photo Annotation and Concept-Based Retrieval Tasks”, ImageClef Lab of CLEF 2011 Conference on Multilingual and Multimodal Information Access Evaluation, Amsterdam, Netherlands, 2011.
	E. Spyromitros-Xioufis, E. Stachtiari, G. Tsoumakas, I. Vlahavas, “A Hybrid Approach for Cold-start Recommendations of Videolectures”, Proceedings ECML/PKDD 2011 Discovery Challenge Workshop, Athens, Greece, 2011.
	A. Fachantidis, I. Partalas, G. Tsoumakas, I. Vlahavas, “Transferring Models in Hybrid Reinforcement Learning Agents”, Proc. Engineering Applications of Neural Networks, Springer Berlin Heidelberg, pp. 162-171, 2011.
	K. Sechidis, G. Tsoumakas, I. Vlahavas, “On the Stratification of Multi-Label Data”, Proceedings of ECML PKDD 2011, Athens, Greece, 2011.
	E. Spyromitros-Xioufis, G. Tsoumakas, I. Vlahavas, “Multi-label Learning Approaches for Music Instrument Recognition”, Proc. 9th International Symposium on Methodologies for Intelligent Systems (ISMIS 2011), Warsaw, Poland, 2011.
	E. Spyromitros-Xioufis, M. Spiliopoulou, G. Tsoumakas, I. Vlahavas, “Dealing with Concept Drift and Class Imbalance in Multi-label Stream Classification”, Proc. 22nd International Conference on Artificial Intelligence (IJCAI 2011), AAAI press, Barcelona, Spain, 2011.
	G. Tzanis, I. Kavakiotis, I. Vlahavas, “PolyA-iEP: A Data Mining Method for the Effective Prediction of Polyadenylation Sites”, Expert Systems with Applications, Elsevier, 38(10), pp. 1239812408, 2011.
	G. Tsoumakas, E. Spyromitros-Xioufis, J. Vilcek, I. Vlahavas, “Mulan: A Java Library for Multi-Label Learning”, Journal of Machine Learning Research, 12, pp. 2411-2414, 2011.
	G. Tsoumakas, I. Katakis, I. Vlahavas, “Random k-Labelsets for Multi-Label Classification”, IEEE Transactions on Knowledge and Data Engineering, IEEE, 23(7), pp. 1079-1089, 2011.
	I. Vlahavas, P. Kefalas, N. Bassiliades, F. Kokkoras, I. Sakellariou, “Artificial Intelligence, 3rd edition (in Greek - Τεχνητή Νοημοσύνη, Γ' Έκδοση)”, Book, Έκδοση/Διάθεση: Εκδόσεις Πανεπιστημίου Μακεδονίας, ISBN 978-960-8396-64-7, 2011.
	Year Total: 12
2010
	I. Vlahavas, N. Bassiliades, “Special issue on Artificial Intelligence Techniques for Pervasive Computing: Preface”, International Journal on Artificial Intelligence Tools, World Scientific, 19(2), pp. 133-135, 2010.
	G. Tsoumakas, E. Spyromitros-Xioufis, J. Vilcek, I. Vlahavas, “Mulan: A Java Library for Multi-Label Learning”, ICML 2010 Workshop on Machine Learning Open Source Software (MLOSS 2010), Demo/Poster Session, Haifa, Israel, 2010.
	G. Nasierding, A. Kouzani, G. Tsoumakas, “A Triple-Random Ensemble Classification Method for Mining Multi-label Data”, Proc. 2010 IEEE International Conference on Data Mining Workshops, pp. 49-56, 2010.
	F. Markatopoulou, G. Tsoumakas, I. Vlahavas, “Instance-Based Ensemble Pruning via Multi-Label Classification”, 22nd International Conference on Tools with Artificial Intelligence, 27-29 October 2010., IEEE, Arras, France, 2010.
	M. Ioannou, G. Sakkas, G. Tsoumakas, I. Vlahavas, “Obtaining Bipartitions from Score Vectors for Multi-Label Classification”, 22nd International Conference on Tools with Artificial Intelligence, 27-29 October 2010., IEEE, Arras, France, 2010.
	I. Partalas, G. Tsoumakas, I. Vlahavas, “An Ensemble Uncertainty Aware Measure for Directed Hill Climbing Ensemble Pruning”, Machine Learning, Springer, 2010.
	G. Tsoumakas, I. Katakis, I. Vlahavas, “Mining Multi-label Data”, Data Mining and Knowledge Discovery Handbook, Part 6, O. Maimon, L. Rokach (Ed.), Springer, 2nd edition, pp. 667-685, 2010.
	I. Katakis, G. Tsoumakas, I. Vlahavas, “Tracking Recurring Contexts using Ensemble Classifiers: An Application to Email Filtering”, Knowledge and Information Systems, Springer, 22(3), pp. 371-391, 2010.
	Year Total: 8
2009
	L. Iliadis, I. Maglogiannis, G. Tsoumakas, I. Vlahavas, M. Bramer, “Artificial Intelligence Applications and Innovations: Proceedings of the 5th IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI'2009)”, ISBN: 978-1441902207, Springer, 2009.
	N. Bassiliades, “AIAI 2009 Workshops Proceedings, Proceedings of the Workshops of the 5th IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI-2009)”, CEUR Workshop Proceedings, ISSN 1613-0073, Vol. 475, pp. 349, Thessaloniki, Greece, April 23-25, 2009.
	N. Bassiliades, I. Antoniades, E. Hatzikos, I. Vlahavas, G. Koutitas, “An Intelligent System for Monitoring and Predicting Water Quality”, Proceedings of the European conference TOWARDS eENVIRONMENT, pp. 534-542, Prague, Czech Republic, March 2009, 2009.
	G. Tsoumakas, A. Dimou, E. Spyromitros-Xioufis, V. Mezaris, I. Kompatsiaris, I. Vlahavas, “Correlation-Based Pruning of Stacked Binary Relevance Models for Multi-Label Learning”, Proceedings of the 1st International Workshop on Learning from Multi-Label Data (MLD'09), G. Tsoumakas, Min-Ling Zhang, Zhi-Hua Zhou (Ed.), pp. 101-116, Bled, Slovenia, 2009.
	G. Tsoumakas, E. Loza Mencía, I. Katakis, S. Park, J. Fürnkrnaz, “On the combination of two decompositive multi-label classification methods”, Workshop on Preference Learning, ECML PKDD 09, Eyke Hüllermeir, Johannes Fürnkranz (Ed.), pp. 114-133, Bled, Slovenia, 2009.
	G. Nasierding, G. Tsoumakas, A. Kouzani, “Clustering Based Multi-Label Classification for Image Annotation and Retrieval”, 2009 IEEE International Conference on Systems, Man, and Cybernetics, IEEE, 2009.
	E. Hatzikos, J. Hätönen, N. Bassiliades, I. Vlahavas, E. Fournou, “Applying adaptive prediction to sea-water quality measurements”, Expert Systems with Applications, Elsevier, Vol. 36, Iss. 3, Part 2, pp. 6773-6779, 2009.
	A. Dimou, G. Tsoumakas, V. Mezaris, I. Kompatsiaris, I. Vlahavas, “An Empirical Study Of Multi-Label Learning Methods For Video Annotation”, 7th International Workshop on Content-Based Multimedia Indexing, IEEE, Chania, Crete, 2009.
	I. Partalas, G. Tsoumakas, K. Tzevanidis, I. Vlahavas, “Transferring Experience in Reinforcement Learning through Task Decomposition”, International Conference on Autonomous Agents and Multiagent Systems, 2009.
	G. Tsoumakas, I. Partalas, I. Vlahavas, “An Ensemble Pruning Primer”, Supervised and Unsupervised Methods and Their Applications to Ensemble Methods (SUEMA 2009), Oleg Okun and Giorgio Valentini (Eds.), Springer Verlag, Volume 245/2009, pp. 1-13, 2009.
	I. Katakis, G. Meditskos, G. Tsoumakas, N. Bassiliades, I. Vlahavas, “On the Combination of Textual and Semantic Descriptions for Automated Semantic Web Service Classification”, Proceedings of the 5th IFIP Conference on Artificial Intelligence Applications and Innovations (AIAI 2009), Springer, Thessaloniki, 2009.
	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, L.C. Rivero, J.H. Door, V.E. Ferraggine (Ed.), IGI Global, 2009.
	I. Partalas, G. Tsoumakas, I. Vlahavas, “Pruning an Ensemble of Classifiers via Reinforcement Learning”, Neurocomputing, Elsevier, 72(7-9), pp. 1900-1909, 2009.
	I. Katakis, G. Tsoumakas, E. Banos, N. Bassiliades, I. Vlahavas, “An Adaptive Personalized News Dissemination System”, Journal of Intelligent Information Systems, Springer, 32 (2), pp. 191-201, 2009.
	Year Total: 14
2008
	F. Kokkoras, E. Lampridou, K. Ntonas, I. Vlahavas, “Summarization of Multiple, Metadata Rich, Product Reviews”, Workshop on Mining Social Data (MSoDa), 18th European Conference on Artificial Intelligence (ECAI '08), Patras, Greece, 2008.
	F. Kokkoras, E. Lampridou, K. Ntonas, I. Vlahavas, “MOpiS: a Multiple Opinion Summarizer”, Proc. 5th Hellenic Conference on Artificial Intelligence, LNAI 5138, J. Darzentas et al. (Ed.), Springer-Verlag Berlin Heidelberg, pp. 110-122, Syros, Greece, 2008.
	I. Katakis, G. Tsoumakas, I. Vlahavas, “Multilabel Text Classification for Automated Tag Suggestion”, Proceedings of the ECML/PKDD 2008 Discovery Challenge, Antwerp, 2008.
	G. Tzanis, I. Kavakiotis, I. Vlahavas, “Polyadenylation Site Prediction Using Interesting Emerging Pattern”, 8th IEEE International Conference on Bioinformatics and Bioengineering, IEEE, Athens, Greece, 2008.
	G. Tsoumakas, I. Katakis, I. Vlahavas, “Effective and Efficient Multilabel Classification in Domains with Large Number of Labels”, Proc. ECML/PKDD 2008 Workshop on Mining Multidimensional Data (MMD'08), Antwerp, Belgium, 2008.
	E. Spyromitros-Xioufis, G. Tsoumakas, I. Vlahavas, “An Empirical Study of Lazy Multilabel Classification Algorithms”, Proc. 5th Hellenic Conference on Artificial Intelligence (SETN 2008), Springer, LNAI Vol.5138, pp. 401-406, Syros, Greece, 2008.
	I. Partalas, I. Feneris, I. Vlahavas, “A Hybrid Multiagent Reinforcement Learning Approach using Strategies and Fusion”, International Journal of Artificial Intelligence Tools (IJAIT), World Scientific, 17 (5), pp. 945-961, 2008.
	K. Trohidis, G. Tsoumakas, G. Kalliris, I. Vlahavas, “Multilabel Classification of Music into Emotions”, Proc. 9th International Conference on Music Information Retrieval (ISMIR 2008), pp. 325-330, Philadelphia, PA, USA, 2008.
	G. Tsoumakas, I. Partalas, I. Vlahavas, “A Taxonomy and Short Review of Ensemble Selection”, ECAI, Workshop on Supervised and Unsupervised Ensemble Methods and Their Applications, Patras, Greece, 2008.
	I. Partalas, G. Tsoumakas, E. Hatzikos, I. Vlahavas, “Greedy Regression Ensemble Selection: Theory and an Application to Water Quality”, Information Sciences, Elsevier, 178(20), pp. 3867-3879, 2008.
	I. Partalas, G. Paliouras, I. Vlahavas, “Reinforcement Learning with Classifier Selection for Focused Crawling”, 18th European Conference on Artificial Intelligence, IOS Press, pp. 759-760, 2008.
	I. Partalas, G. Tsoumakas, I. Vlahavas, “Focused Ensemble Selection: A Diversity-Based Method for Greedy Ensemble Selection”, 18th European Conference on Artificial Intelligence, IOS Press, pp. 117-121, Patras, Greece, 2008.
	I. Katakis, G. Tsoumakas, I. Vlahavas, “An Ensemble of Classifiers for coping with Recurring Contexts in Data Streams”, 18th European Conference on Artificial Intelligence, IOS Press, pp. 763-764, Patras, Greece, 2008.
	S. Bibi, G. Tsoumakas, I. Stamelos, I. Vlahavas, “Regression via Classification applied on Software Defect Prediction”, Expert Systems with Applications, Elsevier, 34(3), pp. 2091-2101, 2008.
	I. Partalas, D. Vrakas, I. Vlahavas, “Reinforcement Learnign and Automated Planning: A Survey”, Artificial Intelligence for Advanced Problem Solving Techniques, D. Vrakas and I. Vlahavas (Eds.), IGI, pp. 148-165, 2008.
	E. Hatzikos, G. Tsoumakas, G. Tzanis, N. Bassiliades, I. Vlahavas, “An Empirical Study of Sea Water Quality Prediction”, Knowledge-Based Systems, Elsevier, 21(6), pp. 471-478, 2008.
	G. Tsoumakas, I. Vlahavas, “Distributed Data Mining”, Encyclopedia of Data Warehousing and Mining - 2nd Edition, John Wang (Ed.), Idea Group Reference, pp. 709-715, 2008.
	Year Total: 17
2007
	I. Partalas, I. Feneris, I. Vlahavas, “Multi-Agent Reinforcement Learning using Strategies and Voting”, Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), (to be presented), IEEE, 2007.
	G. Tzanis, I. Vlahavas, “Accurate Classification of SAGE Data Based on Frequent Patterns of Gene Expression”, Proceedings of the IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), IEEE, Patras, Greece, 2007.
	G. Tzanis, I. Vlahavas, “Mining High Quality Clusters of SAGE Data”, Proceedings of the 2nd VLDB Workshop on Data Mining in Bioinformatics, Vienna, Austria, 2007.
	G. Tsoumakas, I. Vlahavas, “Random k-Labelsets: An Ensemble Method for Multilabel Classification”, Proceedings of the 18th European Conference on Machine Learning (ECML 2007), J.N. Kok, J. Koronacki, R.L. de Mantaras, S. Matwin, D. Mladenič, A. Skowron (Ed.), Springer Verlag, LNAI 4701, pp. 406-417, Warsaw, Poland, 2007.
	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.
	I. Partalas, E. Hatzikos, G. Tsoumakas, I. Vlahavas, “Ensemble Selection for Water Quality Prediction”, Proceedings of the 10th International Conference on Engineering Applications of Neural Networks, Thessaloniki, 2007.
	E. Hatzikos, N. Bassiliades, L. Asmanis, I. Vlahavas, “Monitoring Water Quality through a Telematic Sensor Network and a Fuzzy Expert System”, Expert Systems, Blackwell, 24(3), pp. 143-161, 2007.
	D. Vrakas, G. Tsoumakas, F. Kokkoras, N. Bassiliades, I. Vlahavas, D. Anagnostopoulos, “PASER: A Curricula Synthesis System based on Automated Problem Solving”, International Journal on Teaching and Case Studies, Special Issue on "Information Systems: The New Research Agenda, the Emerging Curriculum and the New Teaching Paradigm", Inderscience, Vol. 1, Nos. 1/2, pp. 159-170, 2007.
	C. Berberidis, I. Vlahavas, “Detection and Prediction of Rare Events in Transaction Databases”, International Journal on Artificial Intelligence Tools, World Scientific Publishing Company, 16(5), pp. 829 - 848, 2007.
	G. Tzanis, 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.
	G. Tsoumakas, I. Katakis, “Multi Label Classification: An Overview”, International Journal of Data Warehousing and Mining, David Taniar (Ed.), Idea Group Publishing, 3(3), pp. 1-13, 2007.
	G. Tsoumakas, I. Vlahavas, “An interoperable and scalable Web-based system for classifier sharing and fusion”, Expert Systems with Applications, Elsevier, 33(3), pp. 716-724, 2007.
	Year Total: 12
2006
	G. Tzanis, C. Berberidis, I. Vlahavas, “A Novel Data Mining Approach for the Accurate Prediction of Translation Initiation Sites”, 7th International Symposium on Biological and Medical Data Analysis, Nicos Maglaveras et al. (Ed.), Springer-Verlag, pp. 92-103, Thessaloniki, Greece, 2006.
	G. Tzanis, C. Berberidis, I. Vlahavas, “On the Discovery of Mutually Exclusive Items in a Market Basket Database”, 2nd ADBIS Workshop on Data Mining and Knowledge Discovery, pp. 1-12, Thessaloniki, Greece, 2006.
	E. Banos, I. Katakis, N. Bassiliades, G. Tsoumakas, I. Vlahavas, “PersoNews: A Personalized News Reader Enhanced by Machine Learning and Semantic Filtering”, 5th International Conference on Ontologies, DataBases, and Applications of Semantics (ODBASE 2006), R. Meersman, Z. Tari (Ed.), Springer-Verlag, pp. 975-982, Montpellier, France, 2006.
	I. Katakis, G. Tsoumakas, I. Vlahavas, “Dynamic Feature Space and Incremental Feature Selection for the Classification of Textual Data Streams”, ECML/PKDD-2006 International Workshop on Knowledge Discovery from Data Streams, pp. 107-116, Berlin, Germany, 2006.
	G. Tzanis, I. Katakis, I. Partalas, I. Vlahavas, “Modern Applications of Machine Learning”, Proceedings of the 1st Annual SEERC Doctoral Student Conference, Thessaloniki, Greece, 2006.
	G. Tsoumakas, I. Katakis, I. Vlahavas, “A Review of Multi-Label Classification Methods”, 2nd ADBIS Workshop on Data Mining and Knowledge Discovery, pp. 99-109, 2006.
	G. Tzanis, I. Vlahavas, “Prediction of Translation Initiation Sites Using Classifier Selection”, Proc. 4th Hellenic Conference on Artificial Intelligence (SETN-06), G. Antoniou, G. Potamias, D. Plexousakis, C. Spyropoulos (Ed.), Springer-Verlag, LNAI 3955, pp. 367-377, Heraklion, Crete, 18-20 May, 2006.
	I. Partalas, G. Tsoumakas, I. Katakis, I. Vlahavas, “Ensemble Pruning using Reinforcement Learning”, Proc. 4th Hellenic Conference on Artificial Intelligence (SETN-06), G. Antoniou, G. Potamias, D. Plexousakis, C. Spyropoulos (Ed.), Springer-Verlag, LNAI 3955, pp. 301-310, Heraklion, Crete, 18-20 May, 2006.
	S. Bibi, G. Tsoumakas, I. Stamelos, I. Vlahavas, “Software Defect Prediction Using Regression via Classification”, Proc. 4th ACS/IEEE International Conference on Computer Systems and Applications, AICCSA '06, (accepted for presentation), pp. 330- 336, 2006.
	I. Katakis, G. Tsoumakas, I. Vlahavas, “Email Mining: Emerging Techniques for Email Management”, Web Data Management Practices: Emerging Techniques and Technologies, Athena Vakali, George Pallis (Ed.), Idea Group Publishing, pp. 219-240, 2006.
	Year Total: 10
2005
	M. Golias, D. Angelides, S. Marnas, D. Vrakas, “Use of Multimedia and the World Wide Web in Civil Engineering Learnin”, Journal of Professional Issues in Engineering Education and Practice, American Society for Civil Engineering, 131 (2), pp. 129-137, 2005.
	E. Hatzikos, L. Anastasakis, N. Bassiliades, I. Vlahavas, “Applying neural networks with active neurons to sea-water quality measurements”, 2nd Int. Scientific Conf. on Computer Science, Plamenka Borovska, Sofoklis Christofordis (Ed.), IEEE Computer Society, Bulgarian Section, 30th Sep-2nd Oct 2005, Halkidiki, Greece, 2005.
	S. Diplaris, G. Tsoumakas, P. Mitkas, I. Vlahavas, “Protein Classification with Multiple Algorithms”, 10th Panhellenic Conference on Informatics (PCI 2005), P. Bozanis and E.N. Houstis (Eds.), Springer-Verlag, LNCS 3746, pp. 448-456, Volos, Greece, 11-13 November, 2005.
	I. Katakis, G. Tsoumakas, I. Vlahavas, “On the Utility of Incremental Feature Selection for the Classification of Textual Data Streams”, 10th Panhellenic Conference on Informatics (PCI 2005), P. Bozanis and E.N. Houstis (Eds.), Springer-Verlag, LNCS 3746, pp. 338-348, Volos, Greece, 11-13 November, 2005.
	G. Tzanis, C. Berberidis, A. Alexandridou, I. Vlahavas, “Improving the Accuracy of Classifiers for the Prediction of Translation Initiation Sites in Genomic Sequences”, 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.
	C. Berberidis, G. Tzanis, I. Vlahavas, “Mining for Contiguous Frequent Itemsets in Transaction Databases”, IEEE 3rd International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS'2005), IEEE, pp. 679-685, Sofia, Bulgaria, 2005.
	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, pp. 35-41, 2005.
	G. Tsoumakas, L. Angelis, I. Vlahavas, “Selective Fusion of Heterogeneous Classifiers”, Intelligent Data Analysis, IOS Press, 9(6), pp. 511-525, 2005.
	D. Vrakas, G. Tsoumakas, N. Bassiliades, I. Vlahavas, “HAPrc: An Automatically Configurable Planning System”, AI Communications, 18 (1), pp. 41-60, 2005.
	C. Berberidis, I. Vlahavas, “Mining for weak periodic signals in time series databases”, Intelligent Data Analysis, Dr. F. Famili (Ed.), IOS Press, 9(1), 2005.
	D. Vrakas, G. Tsoumakas, N. Bassiliades, I. Vlahavas, “Machine Learning for Adaptive Planning”, Intelligent Techniques for Planning, I. Vlahavas and D. Vrakas (Eds.), IDEA GROUP PUBLISHING, Ch. 3, pp. 90-120, 2005.
	F. Kokkoras, N. Bassiliades, I. Vlahavas, “Aggregator: A Knowledge based Comparison Chart Builder for e-Shopping”, Intelligent Knowledge-Based Systems: Business and Technology in the New Millennium, C.T. Leondes (Ed.), Kluwer Academic Publishers, Vol. 1: Knowledge-Based Systems, Ch. 6, pp. 140-163, 2005.
	Year Total: 12
2004
	S. Konias, N. Maglaveras, I. Vlahavas, “Predicting Missing Parts in Time Series Using Uncertainty Theory”, Biological and Medical Data Analysis: 5th International Symposium, ISBMDA 2004, J. M. Barreiro, F. Martin-Sanchez, V. Maojo, et al. (Ed.), Springer-Verlag, 3337, pp. 313-321, Barcelona, Spain, November 18-19, 2004, 2004.
	C. Berberidis, L. Angelis, I. Vlahavas, “PREVENT: An algorithm for mining inter-transactional patterns for the prediction of rare events”, 2nd European Starting AI Researcher Symposium (STAIRS' 04), IOS Press, pp. 128-136, Valencia, Spain, 2004.
	G. Tsoumakas, G. Meditskos, D. Vrakas, N. Bassiliades, I. Vlahavas, “Web Services for Adaptive Planning”, Proc. ECAI04 Workshop on Planning and Scheduling: Bridging Theory to Practice, D. Borrajo (Ed.), IOS Press, Valencia Spain, 2004.
	G. Tsoumakas, I. Katakis, I. Vlahavas, “Effective Voting of Heterogeneous Classifiers”, Proc. European Conference on Machine Learning, ECML 04, Jean-Francois Boulicaut, Floriana Esposito, Fosca Giannoti, Dino Pedreschi (Ed.), LNAI 3201, pp. 465-476, Pisa, Italy, 2004.
	C. Berberidis, L. Angelis, I. Vlahavas, “Inter-Transaction Association Rules Mining for Rare Events Prediction”, Proc. 3rd Hellenic Conference on Artificial Intellligence (SETN '04), Samos, Greece, 2004.
	G. Tsoumakas, D. Vrakas, N. Bassiliades, I. Vlahavas, “Lazy Adaptive Multicriteria Planning”, Proc. 16th European Conference on Artificial Intelligence, ECAI 2004, R. Lopez de Mantaras and L. Saitta (Eds.), IOS Press, pp. 693-697, Valencia, Spain, 2004.
	F. Kokkoras, N. Bassiliades, I. Vlahavas, “Modelling Information Extraction Wrappers with Conceptual Graphs”, Proc. (2nd Volume) 3rd Panhellenic Conference on Artificial Intelligence (SETN'04), Zitis Publications, ISBN 960-431-910-8, 5-8 May 2004, Samos, Greece, 2004.
	G. Tsoumakas, D. Vrakas, N. Bassiliades, I. Vlahavas, “Using the k-nearest problems for adaptive multicriteria planning”, Proc. 3rd Hellenic Conference on Artificial Intellligence (SETN '04), G. Vouros and T. Panayiotopoulos (Eds.), Springer-Verlag, LNAI 3025, pp. 132-141, Samos, Greece, 2004.
	G. Tsoumakas, N. Bassiliades, I. Vlahavas, “A Knowledge-based Web Information System for the Federation of Distributed Classifiers”, Web Information Systems, D. Taniar and W. Rahayu (Eds.), Idea-Group Publishing, Chapter 8, pp. 271-308, 2004.
	G. Tsoumakas, L. Angelis, I. Vlahavas, “Clustering Classifiers for Knowledge Discovery from Physically Distributed Databases”, Data and Knowledge Engineering, Elsevier, 49(3), pp. 223-242, 2004.
	Year Total: 10
2003
	I. Vlahavas, “Preface of Special Issue on Knowledge Discovery from Distributed Information Sources”, Information Sciences, Elsevier, 155(3-4), pp. 179-180, 2003.
	C. Berberidis, I. Vlahavas, “Periodicity Mining in Industrial Data: A Real World Example on Power Data”, First International Conference for Mathematics and Informatics for Industry (MII2003), Thessaloniki, 2003.
	D. Vrakas, G. Tsoumakas, N. Bassiliades, I. Vlahavas, “Learning Rules for Adaptive Planning”, Proc. 13th International Conference on Automated Planning and Scheduling (ICAPS '03), pp. 82-91, Trento, Italy, June 2003, 2003.
	Year Total: 3
2002
	D. Vrakas, G. Tsoumakas, I. Vlahavas, “Towards Adaptive Heuristic Planning through Machine Learning”, Proc. 21st Workshop of the UK Planning and Scheduling Special Interest Group (PlanSIG '02), 2002.
	I. Vlahavas, P. Kefalas, N. Bassiliades, I. Refanidis, F. Kokkoras, I. Sakellariou, “Artificial Intelligence (in Greek - Τεχνητή Νοημοσύνη)”, Book, Gartaganis Publications, ISBN 960-7013-28-X, 2002.
	C. Berberidis, A. Walid, M. Atallah, I. Vlahavas, A. Elmagarmid, “Multiple and Partial Periodicity Mining in Time Series Databases”, Proc. 15th European Conference on Artificial Intelligence (ECAI '02), Frank Van Harmelen (Ed.), IOS Press, pp. 370-374, Lyon, France, 2002.
	G. Tsoumakas, I. Vlahavas, “Effective Stacking of Distributed Classifiers”, Proc. 15th European Conference on Artificial Intelligence (ECAI '02), Frank van Harmelen (Ed.), IOS Press, pp. 340-344, 2002.
	G. Tsoumakas, I. Vlahavas, “Distributed Data Mining of Large Classifier Ensembles”, Proc. (companion volume) 2nd Hellenic Conference on AI (SETN '02), I. Vlahavas, C. Spyropoulos (Ed.), pp. 249-255, Thessaloniki, Greece, 2002.
	C. Berberidis, I. Vlahavas, W. Aref, M. Atallah, A. 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), Springer-Verlag, LNAI 2431, pp. 51-61, 2002.
	Year Total: 6
2001
	G. Tsoumakas, I. Vlahavas, “Fuzzy Meta-Learning: Preliminary Results”, Proc. UK Workshop on Computational Intelligence (UKCI '01), pp. 43-48, 2001.
	Year Total: 1
1999
	M. Karamanlidou, I. Vlahavas, “Stock Miner: A System for Knowledge Discovery and Financial Data”, Proc. ACAI '99 Workshop on Data Mining in Economics, Marketing and Finance, 1999.
	Year Total: 1
1997
	N. Bourbakis, D. Goldman, R. Fermatt, I. Vlahavas, L. Tsoukalas, “Path Planning in a 2-D known Space using Neural Networks and Skeletonization”, Proc. IEEE International Conference on Systems Man and Cybernetics (SMC '97), 1997.
	A. Likartsis, I. Vlahavas, L. Tsoukalas, “A New Hybrid Neural-Genetic Methodology for Improving Learning”, Proc. IEEE 9th International Conference on Tools with Artificial Intelligence (ICTAI '97), 1997.
	Year Total: 2