Veselka Boeva

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Elena TsiporkovaSenior Technology Advisor, ICT & Software Engineering Group, SirrisVerified email at sirris.be
Niklas LavessonProfessor of Software Engineering - Applied AI/ML at Blekinge Institute of TechnologyVerified email at bth.se
Milena AngelovaTechnical University of Sofia, Plovdiv branchVerified email at tu-plovdiv.bg
Håkan GrahnProfessor of Computer Engineering, Blekinge Institute of Technology, SwedenVerified email at bth.se
De Baets BernardGhent UniversityVerified email at ugent.be
Shahrooz AbghariPhD in Computer Science, Blekinge Institute of TechnologyVerified email at bth.se
Anton BorgBlekinge Institute of TechnologyVerified email at bth.se
Elena KostadinovaPhD Student, Technical University of Sofia, branch PlovdivVerified email at tu-plovdiv.bg
Eva García-MartínPhD in Machine Learning. Data Scientist at Ekkono SolutionsVerified email at ekkono.ai
Vishnu Manasa DevagiriPhD Student, Blekinge Tekniska HögskolaVerified email at bth.se
Martin BoldtAssociate professor, Blekinge Institute of Technology, SwedenVerified email at bth.se
Lars LundbergBlekinge Institute of TechnologyVerified email at bth.se
Emiliano CasalicchioSapienza University of Rome - Computer Science Dep.Verified email at uniroma1.it
Anna Hristoskovadr. ir. Anna Hristoskova, SirrisVerified email at sirris.be
Christian NordahlPh.D student in Computer Science, Blekinge Institute of TechnologyVerified email at bth.se
Love EkenbergProfessor of Computer and Systems Sciences, Stockholm UniversityVerified email at dsv.su.se
Michiel DhontData Innovation Scientist, SirrisVerified email at sirris.be
Juhee BaeLecturer, University of SkövdeVerified email at ncsu.edu
Maria RiveiroProfessor of Computer Science, Jönköping UniversityVerified email at ju.se
Elio Ventocilla, Ph.DSkövde UniversityVerified email at his.se

Veselka Boeva

Professor of Computer Science, Blekinge Institute of Technology

Verified email at bth.se - Homepage

artificial intelligence data mining bioinformatics machine learning uncertainty modelling


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Multi-step ranking of alternatives in a multi-criteria and multi-expert decision making environment E Tsiporkova, V Boeva Information Sciences 176 (18), 2673-2697, 2006	97	2006
Detecting serial residential burglaries using clustering A Borg, M Boldt, N Lavesson, U Melander, V Boeva Expert Systems with Applications 41 (11), 5252-5266, 2014	47	2014
Two-pass imputation algorithm for missing value estimation in gene expression time series E Tsiporkova, V Boeva Journal of bioinformatics and computational biology 5 (05), 1005-1022, 2007	32	2007
Fusing time series expression data through hybrid aggregation and hierarchical merge E Tsiporkova, V Boeva Bioinformatics 24 (16), i63-i69, 2008	24	2008
Nonparametric recursive aggregation process E Tsiporkova, V Boeva Kybernetika 40 (1), [51]-70, 2004	23	2004
Dempster–Shafer theory framed in modal logic E Tsiporkova, V Boeva, B De Baets International journal of approximate reasoning 21 (2), 157-175, 1999	23	1999
A formal concept analysis approach to consensus clustering of multi-experiment expression data A Hristoskova, V Boeva, E Tsiporkova BMC bioinformatics 15 (1), 1-16, 2014	20	2014
Energy efficiency in machine learning: A position paper E García Martín 30th Annual Workshop of the Swedish Artificial Intelligence Society SAIS …, 2017	15	2017
Comparison of Clustering Approaches for Gene Expression Data. A Borg, N Lavesson, V Boeva SCAI, 55-64, 2013	14	2013
Clustering approaches for dealing with multiple DNA microarray datasets V Boeva Journal of Computational Science 5 (3), 368-376, 2014	12	2014
A multi-purpose time series data standardization method V Boeva, E Tsiporkova Intelligent Systems: From Theory to Practice, 445-460, 2010	12	2010
Towards a taxonomy for interpretable and interactive machine learning E Ventocilla, T Helldin, M Riveiro, J Bae, V Boeva, G Falkman, ... 2nd Workshop on Explainable AI (XAI-18), 27th International Joint …, 2018	11	2018
Analysis of multiple DNA microarray datasets V Boeva, E Tsiporkova, E Kostadinova Springer Handbook of Bio-/Neuroinformatics, 223-234, 2014	11	2014
An Integrative DTW-based imputation method for gene expression time series data E Kostadinova, V Boeva, L Boneva, E Tsiporkova 2012 6th IEEE International Conference Intelligent Systems, 258-263, 2012	11	2012
A transition logic for schemata conflicts V Boeva, L Ekenberg Data & Knowledge Engineering 51 (3), 277-294, 2004	11	2004
How to measure energy consumption in machine learning algorithms E García-Martín, N Lavesson, H Grahn, E Casalicchio, V Boeva Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018	10	2018
Measuring expertise similarity in expert networks V Boeva, M Krusheva, E Tsiporkova 2012 6th IEEE International Conference Intelligent Systems, 053-057, 2012	10	2012
A Hybrid DTW based method for integration analysis of time series data V Boeva, E Kostadinova 2009 International Conference on Adaptive and Intelligent Systems, 49-54, 2009	9	2009
Dempster's rule of conditioning translated into modal logic E Tsiporkova, B De Baets, V Boeva Fuzzy Sets and Systems 102 (3), 371-383, 1999	9	1999
Semantic-aware expert partitioning V Boeva, L Boneva, E Tsiporkova International Conference on Artificial Intelligence: Methodology, Systems …, 2014	8	2014

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