I. Vlahavas

I. Vlahavas, Aristotelis Lazaridis, Christos Perchanidis, 2022, 2022 International Conference on INnovations in Intelligent SysTems and Applications (INISTA).

Land evaluation — an artificial intelligence approach

Grigorios Tsoumakas, Ioannis Vlahavas, Grigorios Tsoumakas, 2001 .

Deep Reinforcement Learning: A State-of-the-Art Walkthrough

Ioannis P. Vlahavas, Anestis Fachantidis, Aristotelis Lazaridis, 2020, J. Artif. Intell. Res..

Processing Production Rules in DEVICE, and Active Knowledge Base System

Ioannis P. Vlahavas, Nick Bassiliades, I. Vlahavas, 1997, Data Knowl. Eng..

DEVICE: Compiling production rules into event-driven rules using complex events

Ioannis P. Vlahavas, Nick Bassiliades, I. Vlahavas, 1997, Inf. Softw. Technol..

A Neural Entity Coreference Resolution Review pdf

Ioannis Vlahavas, Nikolaos Stylianou, I. Vlahavas, 2019, Expert Syst. Appl..

Ensemble Pruning Using Reinforcement Learning

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2006, SETN.

MULAN: A Java Library for Multi-Label Learning

Grigorios Tsoumakas, Ioannis P. Vlahavas, Eleftherios Spyromitros Xioufis, 2011, J. Mach. Learn. Res..

GRT: A Domain Independent Heuristic for STRIPS Worlds Based on Greedy Regression Tables

Ioannis P. Vlahavas, Ioannis Refanidis, I. Vlahavas, 1999, ECP.

Combining Inter-Review Learning-to-Rank and Intra-Review Incremental Training for Title and Abstract Screening in Systematic Reviews

Grigorios Tsoumakas, Ioannis P. Vlahavas, Athanasios Lagopoulos, 2017, CLEF.

Multi-target regression via input space expansion: treating targets as inputs

Grigorios Tsoumakas, Ioannis P. Vlahavas, William Groves, 2012, Machine Learning.

Multi-target regression via input space expansion: treating targets as inputs pdf

Grigorios Tsoumakas, Ioannis P. Vlahavas, William Groves, 2012, Machine Learning.

A Non-Uniform Data Fragmentation Strategy for Parallel Main-Menory Database Systems

Ioannis P. Vlahavas, Nick Bassiliades, I. Vlahavas, 1995, VLDB.

Regression via Classification applied on software defect estimation

Ioannis Stamelos, Grigorios Tsoumakas, Ioannis P. Vlahavas, 2008, Expert Syst. Appl..

An Empirical Study of Lazy Multilabel Classification Algorithms

Grigorios Tsoumakas, Ioannis P. Vlahavas, Eleftherios Spyromitros Xioufis, 2008, SETN.

Intelligent techniques for planning

Ioannis Vlahavas, Dimitris Vrakas, I. Vlahavas, 2004 .

Mining Frequent Patterns and Association Rules From Biological Data

Ioannis Vlahavas, Ioannis Kavakiotis, George Tzanis, 2013 .

Machine Learning and Data Mining in Bioinformatics

Ioannis Vlahavas, George Tzanis, Christos Berberidis, 2009 .

Pattern discovery for microsatellite genome analysis

Ioannis P. Vlahavas, Ioannis Kavakiotis, Evangelos Konstantinidis, 2014, Comput. Biol. Medicine.

Pruning an ensemble of classifiers via reinforcement learning

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2009, Neurocomputing.

Model-based reinforcement learning for humanoids: A study on forming rewards with the iCub platform

Angelo Cangelosi, Ioannis P. Vlahavas, Anestis Fachantidis, 2013, 2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB).

Biological Data Mining

Ioannis P. Vlahavas, George Tzanis, Christos Berberidis, 2007 .

Integrating multiple immunogenetic data sources for feature extraction and mining somatic hypermutation patterns: the case of “towards analysis” in chronic lymphocytic leukaemia

Grigorios Tsoumakas, Ioanna Chouvarda, Nicos Maglaveras, 2016, BMC Bioinformatics.

Polyadenylation site prediction using PolyA-iEP method.

Ioannis Vlahavas, Ioannis Kavakiotis, George Tzanis, 2014, Methods in molecular biology.

MACLP: multi agent constraint logic programming

Ioannis P. Vlahavas, I. Vlahavas, 2002, Inf. Sci..

Mining Multi-label Data

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Katakis, 2010, Data Mining and Knowledge Discovery Handbook.

AUTH-Atypon at BioASQ 3: Large-Scale Semantic Indexing in Biomedicine

Yannis Papanikolaou, Grigorios Tsoumakas, Ioannis P. Vlahavas, 2015, CLEF.

Transfer Learning in Multi-Agent Reinforcement Learning Domains

Ioannis P. Vlahavas, Ioannis Partalas, Georgios Boutsioukis, 2011, EWRL.

The GRT Planning System: Backward Heuristic Construction in Forward State-Space Planning pdf

Ioannis P. Vlahavas, Ioannis Refanidis, I. Vlahavas, 2001, J. Artif. Intell. Res..

"Cultures in negotiation": teachers' acceptance/resistance attitudes considering the infusion of technology into schools

Ioannis P. Vlahavas, Andreas S. Pomportsis, Stavros N. Demetriadis, 2003, Comput. Educ..

Clustering classifiers for knowledge discovery from physically distributed databases

Lefteris Angelis, Grigorios Tsoumakas, Ioannis P. Vlahavas, 2004, Data Knowl. Eng..

E-DEVICE: An Extensible Active Knowledge Base System with Multiple Rule Type Support

Ioannis P. Vlahavas, Ahmed K. Elmagarmid, Nick Bassiliades, 2000, IEEE Trans. Knowl. Data Eng..

Parallel management of large deductive databases in a multi-processor environment

Ioannis Vlahavas, Nick Bassiliades, C. Maciazek, 1994, Proceedings of MELECON '94. Mediterranean Electrotechnical Conference.

Protein Classification with Multiple Algorithms

Grigorios Tsoumakas, Ioannis P. Vlahavas, Pericles A. Mitkas, 2005, Panhellenic Conference on Informatics.

Selective fusion of heterogeneous classifiers

Lefteris Angelis, Grigorios Tsoumakas, Ioannis P. Vlahavas, 2005, Intell. Data Anal..

Effective Voting of Heterogeneous Classifiers

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Katakis, 2004, ECML.

LionForests: local interpretation of random forests

Grigorios Tsoumakas, I. Vlahavas, Nick Bassiliades, 2019, NeHuAI@ECAI.

A Framework for Multi-Criteria Plan Evaluation in Heuristic State-Space Planning

Ioannis Vlahavas, Ioannis Refanidis, I. Vlahavas, 2007 .

Multiobjective heuristic state-space planning

Ioannis P. Vlahavas, Ioannis Refanidis, I. Vlahavas, 2003, Artif. Intell..

The MO-GRT System : Heuristic Planning with Multiple Criteria

Ioannis Vlahavas, Ioannis Refanidis, I. Vlahavas, 2002 .

PaaSport semantic model: An ontology for a platform-as-a-service semantically interoperable marketplace

Georgios Meditskos, Ioannis P. Vlahavas, Nick Bassiliades, 2017, Data Knowl. Eng..

Predicting Missing Values in a Home Care Database Using an Adaptive Uncertainty Rule Method

N Maglaveras, I Vlahavas, G Gogou, 2005, Methods of Information in Medicine.

Applying a Distributed CLP Platform to a Workforce Management Problem

Ioannis Vlahavas, Ilias Sakellariou, Fotios Kokkoras, 2003 .

On the Stratification of Multi-label Data

Grigorios Tsoumakas, Ioannis P. Vlahavas, Konstantinos Sechidis, 2011, ECML/PKDD.

Dynamic ensemble pruning based on multi-label classification

Grigorios Tsoumakas, Ioannis P. Vlahavas, Fotini Markatopoulou, 2015, Neurocomputing.

E.T.: Entity-Transformers. Coreference augmented Neural Language Model for richer mention representations via Entity-Transformer blocks pdf

Ioannis Vlahavas, Nikolaos Stylianou, I. Vlahavas, 2020, CRAC.

An Intelligent Modular Water Monitoring IoT System for Real-Time Quantitative and Qualitative Measurements

I. Vlahavas, F. Stergiopoulos, Eirini Aivazidou, 2023, Sustainability.

eLPA: An e-Learner's Personal Assistant

Ioannis Vlahavas, Fotios Kokkoras, I. Vlahavas, 2002 .

A Knowledge Based Approach on Educational Metadata Use

Ioannis P. Vlahavas, Demetrios G. Sampson, Fotis Kokkoras, 2001, Panhellenic Conference on Informatics.

A survey of service composition in ambient intelligence environments

Thanos G. Stavropoulos, Ioannis P. Vlahavas, Dimitris Vrakas, 2013, Artificial Intelligence Review.

A Comprehensive Study Over VLAD and Product Quantization in Large-Scale Image Retrieval

Grigorios Tsoumakas, Ioannis Vlahavas, Symeon Papadopoulos, 2014, IEEE Transactions on Multimedia.

Serious Game Development for the Diagnosis of Major Depressive Disorder Cases Using Machine Learning Methods (short paper)

I. Vlahavas, Aristotelis Lazaridis, Athanasios Tsionas, 2020, SETN Workshops.

Monitoring water quality through a telematic sensor network and a fuzzy expert system

Ioannis P. Vlahavas, Nick Bassiliades, Evaggelos V. Hatzikos, 2007, Expert Syst. J. Knowl. Eng..

An Intelligent System for WAN Management

Ioannis Vlahavas, Nick Bassiliades, Ilias Sakellariou, 2002 .

ExperNet: An Intelligent Multiagent System for WAN Management

Sascha Ossowski, Ioannis P. Vlahavas, Nick Bassiliades, 2002, IEEE Intell. Syst..

Random K-labelsets for Multilabel Classification

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Katakis, 2022 .

AUTOMATING THE EVALUATION OF EDUCATIONAL SOFTWARE

Ioannis Stamelos, Ioannis Vlahavas, Panagiotis Katsaros, 2011 .

Knowledge based evaluation of software systems: a case study

Ioannis Stamelos, Alexis Tsoukiàs, Ioannis Vlahavas, 2000, Inf. Softw. Technol..

An Adaptable Framework for Educational Software Evaluation

A. Pombortsis, I. Stamelos, P. Katsaros, 2000 .

ESSE: an expert system for software evaluation

Ioannis Stamelos, Ioannis P. Vlahavas, Alexis Tsoukiàs, 1999, Knowl. Based Syst..

An interoperable and scalable Web-based system for classifier sharing and fusion

Grigorios Tsoumakas, Ioannis P. Vlahavas, Grigorios Tsoumakas, 2007, Expert Syst. Appl..

A Knowledge-based Web Information System for the Federation of Distributed Classifiers

Grigorios Tsoumakas, Ioannis Vlahavas, Nick Bassiliades, 2004 .

Lefteris Angelis, Grigorios Tsoumakas, Ioannis Vlahavas, 2002 .

Improving Diversity in Image Search via Supervised Relevance Scoring

Yiannis Kompatsiaris, Ioannis P. Vlahavas, Symeon Papadopoulos, 2015, ICMR.

A System for Energy Savings in an Ambient Intelligence Environment

Thanos G. Stavropoulos, Ioannis P. Vlahavas, Dimitris Vrakas, 2011, ICT-GLOW.

On the Discovery of Weak Periodicities in Large Time Series

Walid G. Aref, Mikhail J. Atallah, Ioannis P. Vlahavas, 2002, PKDD.

Methods and Applications of Artificial Intelligence

Ioannis Vlahavas, Constantine D. Spyropoulos, I. Vlahavas, 2002, Lecture Notes in Computer Science.

Artificial Intelligence for Advanced Problem Solving Techniques

Ioannis Vlahavas, Dimitris Vrakas, I. Vlahavas, 2008 .

Reinforcement Learning and Automated Planning: A Survey

Ioannis Vlahavas, Ioannis Partalas, Dimitris Vrakas, 2008 .

Multi-target Regression via Random Linear Target Combinations pdf

Grigorios Tsoumakas, Ioannis P. Vlahavas, Eleftherios Spyromitros Xioufis, 2014, ECML/PKDD.

Tracking recurring contexts using ensemble classifiers: an application to email filtering

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Katakis, 2009, Knowledge and Information Systems.

Machine Learning for Adaptive Planning

Grigorios Tsoumakas, Ioannis Vlahavas, Dimitris Vrakas, 2005 .

HAPRC: an automatically configurable planning system

Grigorios Tsoumakas, Ioannis P. Vlahavas, Nick Bassiliades, 2005, AI Commun..

Multi-label classification of music by emotion

Grigorios Tsoumakas, Ioannis P. Vlahavas, George Kalliris, 2011, EURASIP J. Audio Speech Music. Process..

Multi-Label Classification of Music into Emotions

Grigorios Tsoumakas, Ioannis P. Vlahavas, George Kalliris, 2008, ISMIR.

InterBase-KB: Integrating a Knowledge Base System with a Multidatabase System for Data Warehousing

Ioannis P. Vlahavas, Ahmed K. Elmagarmid, Elias N. Houstis, 2003, IEEE Trans. Knowl. Data Eng..

Active Knowledge-Based Systems

Ioannis Vlahavas, Nick Bassiliades, I. Vlahavas, 2000 .

E-DEVICE: An Extensible Knowledge Base System with Multiple Rule Support

Ahmed K. Elmagarmid, Ioannis Vlahavas, Nick Bassiliades, 1997 .

InterBase (KB): A Knowledge-based Multidatabase System for Data Warehousing

Ahmed K. Elmagarmid, Elias N. Houstis, Ioannis Vlahavas, 1997 .

Dealing with Concept Drift and Class Imbalance in Multi-Label Stream Classification

Grigorios Tsoumakas, Myra Spiliopoulou, Ioannis P. Vlahavas, 2011, IJCAI.

Large-Scale Semantic Indexing of Biomedical Publications

Grigorios Tsoumakas, Ioannis P. Vlahavas, Manos Laliotis, 2013, BioASQ@CLEF.

TransforMED: End-to-Εnd Transformers for Evidence-Based Medicine and Argument Mining in medical literature

I. Vlahavas, Nikolaos Stylianou, 2021, J. Biomed. Informatics.

Reinforcement learning agents providing advice in complex video games

Ioannis P. Vlahavas, Matthew E. Taylor, Anestis Fachantidis, 2014, Connect. Sci..

MOpiS: A Multiple Opinion Summarizer

Ioannis P. Vlahavas, Fotis Kokkoras, Konstantinos Ntonas, 2008, SETN.

An adaptive personalized news dissemination system

Grigorios Tsoumakas, Ioannis P. Vlahavas, Nick Bassiliades, 2009, Journal of Intelligent Information Systems.

An Integrated Approach to Automated Semantic Web Service Composition through Planning

Mara Nikolaidou, Ioannis P. Vlahavas, Nick Bassiliades, 2012, IEEE Transactions on Services Computing.

Rule-based approaches for energy savings in an ambient intelligence environment

Thanos G. Stavropoulos, Ioannis P. Vlahavas, Nick Bassiliades, 2015, Pervasive Mob. Comput..

EBM+: Advancing Evidence-Based Medicine via two level automatic identification of Populations, Interventions, Outcomes in medical literature

Ioannis Vlahavas, Dimitrios G Goulis, Nikolaos Stylianou, 2020, Artif. Intell. Medicine.

Effective Stacking of Distributed Classifiers

Grigorios Tsoumakas, Ioannis P. Vlahavas, Grigorios Tsoumakas, 2002, ECAI.

GENEREIT: generating multi-talented reinforcement learning agents

I. Vlahavas, Aristotelis Lazaridis, A. Lazaridis, 2023, International Journal of Information Technology.

aWESoME: A web service middleware for ambient intelligence

Thanos G. Stavropoulos, Ioannis P. Vlahavas, Dimitris Vrakas, 2013, Expert Syst. Appl..

DR-DEVICE: A Defeasible Logic System for the Semantic Web

Ioannis P. Vlahavas, Nick Bassiliades, Grigoris Antoniou, 2004, PPSWR.

Semantic Awareness in Automated Web Service Composition through Planning

Ioannis P. Vlahavas, Nick Bassiliades, Dimosthenis Anagnostopoulos, 2010, SETN.

TRES: Identification of Discriminatory and Informative SNPs from Population Genomic Data.

Grigorios Tsoumakas, I. Vlahavas, M. Groenen, 2015, The Journal of heredity.

Multi-target regression via output space quantization

Ioannis P. Vlahavas, Konstantinos Sechidis, Eleftherios Spyromitros Xioufis, 2020, 2020 International Joint Conference on Neural Networks (IJCNN).

Inter-Transaction Association Rules Mining for Rare Events Prediction

Lefteris Angelis, Ioannis Vlahavas, Christos Berberidis, 2004 .

On the Utility of Incremental Feature Selection for the Classification of Textual Data Streams

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Katakis, 2005, Panhellenic Conference on Informatics.

Short-term Load Forecasting With Clustered Hybrid Models Based On Hour Granularity

Grigorios Tsoumakas, I. Vlahavas, Stamatis Karlos, 2022, Hellenic Conference on Artificial Intelligence.

Improved Biomedical Entity Recognition via Longer Context Modeling

Ioannis P. Vlahavas, Nikolaos Stylianou, Panagiotis Kosmoliaptsis, 2021, AIAI.

System Architecture for a Smart University Building

Thanos G. Stavropoulos, George Koutitas, Ioannis P. Vlahavas, 2010, ICANN.

FIFS: A data mining method for informative marker selection in high dimensional population genomic data

Ioannis P. Vlahavas, Ioannis Kavakiotis, Patroklos Samaras, 2017, Comput. Biol. Medicine.

Transforming Drug-Drug Interaction Extraction from Biomedical Literature

I. Vlahavas, Dimitrios Zaikis, Stylianos Kokkas, 2022, SETN.

A prediction model of passenger demand using AVL and APC data from a bus fleet

Grigorios Tsoumakas, Ioannis P. Vlahavas, Anestis Fachantidis, 2015, Panhellenic Conference on Informatics.

Drug-Drug Interaction Classification Using Attention Based Neural Networks

Ioannis Vlahavas, Dimitrios Zaikis, I. Vlahavas, 2020, SETN.

Detection and Prediction of Rare Events in Transaction Databases

Ioannis P. Vlahavas, Christos Berberidis, I. Vlahavas, 2007, Int. J. Artif. Intell. Tools.

Obtaining Bipartitions from Score Vectors for Multi-Label Classification

Grigorios Tsoumakas, Ioannis P. Vlahavas, Marios Ioannou, 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.

Instance-Based Ensemble Pruning via Multi-Label Classification

Grigorios Tsoumakas, Ioannis P. Vlahavas, Fotini Markatopoulou, 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.

An Empirical Study of Multi-label Learning Methods for Video Annotation

Yiannis Kompatsiaris, Grigorios Tsoumakas, Ioannis P. Vlahavas, 2009, 2009 Seventh International Workshop on Content-Based Multimedia Indexing.

Random k-Labelsets for Multilabel Classification

Grigorios Tsoumakas, I. Katakis, I. Vlahavas, 2011, IEEE Transactions on Knowledge and Data Engineering.

Large-scale online semantic indexing of biomedical articles via an ensemble of multi-label classification models

Grigorios Tsoumakas, I. Vlahavas, Yannis Papanikolaou, 2017, J. Biomed. Semant..

Aristoxenus at SemEval-2023 Task 4: A Domain-Adapted Ensemble Approach to the Identification of Human Values behind Arguments

I. Vlahavas, Dimitrios Zaikis, Stefanos D. Stefanidis, 2023, SEMEVAL.

Multiple and Partial Periodicity Mining in Time Series Databases

Walid G. Aref, Mikhail J. Atallah, Ioannis P. Vlahavas, 2002, ECAI.

Adipose Tissue as a Biomarker in Data Mining Predictive Models of Metabolic Pathophysiologies

I. Vlahavas, Ioannis Kavakiotis, O. Tsave, 2017, BHI 2017.

Immunoglobulin heavy variable (IGHV) genes and alleles: new entities, new names and implications for research and prognostication in chronic lymphocytic leukaemia

I. Vlahavas, K. Stamatopoulos, I. Chouvarda, 2014, Immunogenetics.

Lucy-SKG: Learning to Play Rocket League Efficiently Using Deep Reinforcement Learning

I. Vlahavas, A. Lazaridis, V. Moschopoulos, 2023, ArXiv.

An ensemble uncertainty aware measure for directed hill climbing ensemble pruning

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2010, Machine Learning.

An Ensemble Pruning Primer

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2009, Applications of Supervised and Unsupervised Ensemble Methods.

A semantic recommendation algorithm for the PaaSport platform-as-a-service marketplace

Georgios Meditskos, Ioannis P. Vlahavas, Nick Bassiliades, 2017, Expert Syst. Appl..

Greedy regression ensemble selection: Theory and an application to water quality prediction

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2008, Inf. Sci..

Communicating sequential processes for distributed constraint satisfaction

Ioannis P. Vlahavas, Ilias Sakellariou, Ivan Futó, 2006, Inf. Sci..

CSPCONS: A Communicating Sequential Prolog with Constraints

Ioannis P. Vlahavas, Ilias Sakellariou, Ivan Futó, 2002, SETN.

Sector-level sentiment analysis with deep learning

I. Vlahavas, E. Kouloumpris, Ioannis Almalis, 2022, Knowl. Based Syst..

An empirical study on the combination of surf features with VLAD vectors for image search

Yiannis Kompatsiaris, Grigorios Tsoumakas, Ioannis P. Vlahavas, 2012, 2012 13th International Workshop on Image Analysis for Multimedia Interactive Services.

Transferring experience in reinforcement learning through task decomposition

Grigorios Tsoumakas, Ioannis P. Vlahavas, Ioannis Partalas, 2009, AAMAS.

Large-scale online semantic indexing of biomedical articles via an ensemble of multi-label classification models

Yannis Papanikolaou, Grigorios Tsoumakas, Ioannis P. Vlahavas, 2017, Journal of Biomedical Semantics.

An ontology-based planning system for e-course generation

Ioannis P. Vlahavas, Nick Bassiliades, Efstratios Kontopoulos, 2008, Expert Syst. Appl..

Markowitz Random Forest: Weighting Random Forest Trees with Modern Portfolio Theory

I. Vlahavas, E. Kouloumpris, 2022, Social Science Research Network.

A Hybrid Multiagent Reinforcement Learning Approach Using Strategies and Fusion

Ioannis P. Vlahavas, Ioannis Partalas, Ioannis Feneris, 2008, Int. J. Artif. Intell. Tools.

Reinforcement Learning with Classifier Selection for Focused Crawling

Ioannis P. Vlahavas, Georgios Paliouras, Ioannis Partalas, 2008, ECAI.

StackTIS: A stacked generalization approach for effective prediction of translation initiation sites

Ioannis P. Vlahavas, George Tzanis, Christos Berberidis, 2012, Comput. Biol. Medicine.

Combining deep reinforcement learning with technical analysis and trend monitoring on cryptocurrency markets

I. Vlahavas, E. Kouloumpris, Vasileios Kochliaridis, 2023, Neural Computing and Applications.

Integrating multiple immunogenetic data sources for feature extraction and mining somatic hypermutation patterns: the case of “towards analysis” in chronic lymphocytic leukaemia

Grigorios Tsoumakas, I. Vlahavas, K. Stamatopoulos, 2016, BMC Bioinformatics.

A RISC prolog machine architecture

Constantin Halatsis, J. Vlahavas, I. Vlahavas, 1987, Microprocess. Microprogramming.

Web Service Composition Using a Deductive XML Rule Language

Ioannis P. Vlahavas, Nick Bassiliades, Dimosthenis Anagnostopoulos, 2005, Distributed and Parallel Databases.

A Knowledge-based Framework for Building Web Service Domains

Ioannis Vlahavas, Nick Bassiliades, I. Vlahavas, 2003 .

Distributed singleton consistency

Ioannis P. Vlahavas, Ilias Sakellariou, I. Vlahavas, 2004, J. Exp. Theor. Artif. Intell..

Simple Distributed Filtering on a CLP Platform

Ioannis Vlahavas, Ilias Sakellariou, I. Vlahavas, 2004 .

Information Theoretic Multi-Target Feature Selection via Output Space Quantization †

Ioannis P. Vlahavas, Konstantinos Sechidis, Eleftherios Spyromitros Xioufis, 2019, Entropy.

MLKD's Participation at the CLEF 2011 Photo Annotation and Concept-Based Retrieval Tasks

Grigorios Tsoumakas, Ioannis P. Vlahavas, Konstantinos Sechidis, 2011, CLEF.

Deploying a Semantically-Enabled Content Management System in a State University

Ioannis P. Vlahavas, Nick Bassiliades, Efstratios Kontopoulos, 2010, EGOVIS.

Combining progression and regression in state-space heuris-tic planning

Ioannis Vlahavas, Dimitris Vrakas, I. Vlahavas, 2014 .

HYBRID ACE: COMBINING SEARCH DIRECTIONS FOR HEURISTIC PLANNING

Ioannis P. Vlahavas, Dimitris Vrakas, I. Vlahavas, 2005, Comput. Intell..

A Heuristic for Planning Based on Action Evaluation

Ioannis P. Vlahavas, Dimitris Vrakas, I. Vlahavas, 2002, AIMSA.

The GRT Planner: New Results

Ioannis P. Vlahavas, Ioannis Refanidis, I. Vlahavas, 2000, Local Search for Planning and Scheduling.

Finding Diverse Images at MediaEval 2014

I. Vlahavas, Y. Kompatsiaris, S. Papadopoulos, 2014 .

M ULAN : A Java Library for Multi-Label Learning

Eleftherios Spyromitros Xioufis, Grigorios Tsoumakas, I. Vlahavas, 2011 .

A Visualization Environment for Planning

Ioannis P. Vlahavas, Dimitris Vrakas, I. Vlahavas, 2005, Int. J. Artif. Intell. Tools.

VLEPpO: a Visual Language for Problem Representation

Ioannis Vlahavas, Nick Bassiliades, Dimosthenis Anagnostopoulos, 2007 .

An empirical study on sea water quality prediction

Grigorios Tsoumakas, Ioannis P. Vlahavas, Nick Bassiliades, 2008, Knowl. Based Syst..

R-DEVICE: An Object-Oriented Knowledge Base for RDF Metadata

Ioannis P. Vlahavas, Nick Bassiliades, I. Vlahavas, 2006, Int. J. Semantic Web Inf. Syst..

R-DEVICE: A Deductive RDF Rule Language

Ioannis P. Vlahavas, Nick Bassiliades, I. Vlahavas, 2004, RuleML.

R-DEVICE: an Object-Oriented Knowledge Base System for RDF Metadata

Ioannis Vlahavas, Nick Bassiliades, I. Vlahavas, 2006 .

PersoNews: A Personalized News Reader Enhanced by Machine Learning and Semantic Filtering

Grigorios Tsoumakas, Ioannis P. Vlahavas, Nick Bassiliades, 2006, OTM Conferences.

Ensemble Approaches for Large-Scale Multi-Label Classification and Question Answering in Biomedicine

Yannis Papanikolaou, Grigorios Tsoumakas, Ioannis P. Vlahavas, 2014, CLEF.

PolyA-iEP: A data mining method for the effective prediction of polyadenylation sites

Ioannis P. Vlahavas, Ioannis Kavakiotis, George Tzanis, 2011, Expert Syst. Appl..

Polyadenylation site prediction using interesting emerging patterns

Ioannis P. Vlahavas, Ioannis Kavakiotis, George Tzanis, 2008, 2008 8th IEEE International Conference on BioInformatics and BioEngineering.

Comfresh: A Common Framework for Expert Systems and Hypertext

Ioannis P. Vlahavas, Fotis Kokkoras, I. Vlahavas, 1995, Inf. Process. Manag..