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2003

Feature extraction for classification in the data mining process

Pechenizkiy, M., Puuronen, S. & Tsymbal, A., 2003, In : International Journal on Information Theories and Applications. 10, 1, p. 271-278

Research output: Contribution to journalArticleAcademicpeer-review

2005

Diversity in search strategies for ensemble feature selection

Tsymbal, A., Pechenizkiy, M. & Cunningham, P., 2005, In : Information Fusion. 6, 1, p. 83-98

Research output: Contribution to journalArticleAcademicpeer-review

225 Citations (Scopus)
2006

Local dimensionality reduction and supervised learning within natural clusters for biomedical data analysis

Pechenizkiy, M., Tsymbal, A. & Puuronen, S., 2006, In : IEEE Transactions on Information Technology in Biomedicine. 10, 3, p. 533-539

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)

On combining principal components with Fisher's linear discriminants for supervised learning

Pechenizkiy, M., Tsymbal, A. & Puuronen, S., 2006, In : Foundations of Computing and Decision Sciences. 31, 1, p. 59-73

Research output: Contribution to journalArticleAcademicpeer-review

2007

Feature extraction for dynamic integration of classifiers

Pechenizkiy, M., Tsymbal, A., Puuronen, S. & Patterson, D. W., 2007, In : Fundamenta Informaticae. 77, 3, p. 243-275

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)

Feedback adaptation in web-based learning systems

Vasilyeva, E., Puuronen, S., Pechenizkiy, M. & Räsänen, P., 2007, In : International Journal of Continuing Engineering Education and Lifelong Learning. 17, 4-5, p. 337-357

Research output: Contribution to journalArticleAcademicpeer-review

29 Citations (Scopus)
2008

Dynamic integration of classifiers for handling concept drift

Tsymbal, A., Pechenizkiy, M., Cunningham, P. & Puuronen, S., 2008, In : Information Fusion. 9, 1, p. 56-68

Research output: Contribution to journalArticleAcademicpeer-review

130 Citations (Scopus)

Towards more relevance-oriented data mining research

Pechenizkiy, M., Puuronen, S. & Tsymbal, A., 2008, In : Intelligent Data Analysis. 12, 2, p. 237-249

Research output: Contribution to journalArticleAcademicpeer-review

6 Citations (Scopus)
1 Downloads (Pure)
2009

AH 12 years later: a comprehensive survey of adaptive hypermedia methods and techniques

Knutov, E., Bra, de, P. M. E. & Pechenizkiy, M., 2009, In : New Review of Hypermedia and Multimedia. 15, 1, p. 5-38

Research output: Contribution to journalArticleAcademicpeer-review

136 Citations (Scopus)
7 Downloads (Pure)

Online mass flow prediction in CFB boilers with explicit detection of sudden concept drift

Pechenizkiy, M., Bakker, J., Zliobaite, I., Ivannikov, A. & Kärkkäinen, T., 2009, In : SIGKDD Explorations. 11, 2, p. 109-116

Research output: Contribution to journalArticleAcademicpeer-review

2010

Knowledge discovery and computer-based decision support in biomedicine (Guest editorial)

Soda, P., Pechenizkiy, M., Tortorella, F. & Tsymbal, A., 2010, In : Artificial Intelligence in Medicine. 50, 1, p. 1-2

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)
2011

Generic Adaptation Framework : a process-oriented perspective

Knutov, E., De Bra, P. M. E. & Pechenizkiy, M., 2011, In : Journal of Digital Information. 12, 1, 22 p.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access
File
94 Downloads (Pure)
2012

Beating the baseline prediction in food sales : how intelligent an intelligent predictor is?

Zliobaite, I., Bakker, J. & Pechenizkiy, M., 2012, In : Expert Systems with Applications. 39, 1, p. 806-815

Research output: Contribution to journalArticleAcademicpeer-review

25 Citations (Scopus)

Introduction to the special section on educational data mining

Calders, T. G. K. & Pechenizkiy, M., 2012, In : SIGKDD Explorations. 13, 2, p. 3-6

Research output: Contribution to journalArticleAcademic

6 Downloads (Pure)

ReliefF-MI : an extension of ReliefF to multiple instance learning

Zafra, A., Pechenizkiy, M. & Ventura, S., 2012, In : Neurocomputing. 75, 1, p. 210-218

Research output: Contribution to journalArticleAcademicpeer-review

20 Citations (Scopus)
1 Downloads (Pure)

Trends in computer-based medical systems

Soda, P., Antani, S., Tortorella, F., Cannataro, M., Pechenizkiy, M. & Tsymbal, A., 2012, In : SIGHIT Record. 2, 2, p. 46-50

Research output: Contribution to journalArticleAcademic

2013

A comparative study of dimensionality reduction techniques to enhance trace clustering performances

Song, M. S., Yang, H., Siadat, S. H. & Pechenizkiy, M., 2013, In : Expert Systems with Applications. 40, 9, p. 3722-3737

Research output: Contribution to journalArticleAcademicpeer-review

33 Citations (Scopus)
2 Downloads (Pure)

HyDR-MI : A hybrid algorithm to reduce dimensionality in multiple instance learning

Zafra, A., Pechenizkiy, M. & Ventura, S., 2013, In : Information Sciences. 222, p. 282-301

Research output: Contribution to journalArticleAcademicpeer-review

16 Citations (Scopus)

Predictive handling of asynchronous concept drifts in distributed environments

Ang, H. H., Gopalkrishnan, V., Zliobaite, I., Pechenizkiy, M. & Hoi, S. C. H., 2013, In : IEEE Transactions on Knowledge and Data Engineering. 25, 10, p. 2343-2365 13 p.

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Scopus)
2 Downloads (Pure)
2014

A survey on concept drift adaptation

Gama, J., Zliobaite, I., Bifet, A., Pechenizkiy, M. & Bouchachia, A., 2014, In : ACM Computing Surveys. 46, 4, p. 44/1-37 37 p., 44.

Research output: Contribution to journalArticleAcademicpeer-review

878 Citations (Scopus)
1 Downloads (Pure)

Dealing with concept drifts in process mining

Jagadeesh Chandra Bose, R. P., Aalst, van der, W. M. P., Zliobaite, I. & Pechenizkiy, M., 2014, In : IEEE Transactions on Neural Networks and Learning Systems. 25, 1, p. 154-171

Research output: Contribution to journalArticleAcademicpeer-review

87 Citations (Scopus)
2 Downloads (Pure)
2015

Introduction into sparks of the learning analytics future

Pechenizkiy, M. & Gasevic, D., 2015, In : Journal of Learning Analytics. 1, 3, p. 145-149 5 p.

Research output: Contribution to journalArticleAcademic

Open Access
File
48 Downloads (Pure)
2016

A survey on using domain and contextual knowledge for human activity recognition in video streams

Onofri, L., Soda, P., Pechenizkiy, M. & Iannello, G., 2016, In : Expert Systems with Applications. 63, p. 97-111

Research output: Contribution to journalArticleAcademicpeer-review

34 Citations (Scopus)
1 Downloads (Pure)

Mining exceptional relationships with grammar-guided genetic programming

Luna, J. M., Pechenizkiy, M. & Ventura, S., Jun 2016, In : Knowledge and Information Systems. 47, 3, p. 571-594 24 p.

Research output: Contribution to journalArticleAcademicpeer-review

9 Citations (Scopus)
5 Downloads (Pure)

Speeding-up association rule mining with inverted index compression

Luna, J. M., Cano, A., Pechenizkiy, M. & Ventura, S., 2016, In : IEEE Transactions on Cybernetics. 46, 12, p. 3059-3072

Research output: Contribution to journalArticleAcademicpeer-review

22 Citations (Scopus)
2017

A white-box anomaly-based framework for database leakage detection

Costante, E., den Hartog, J., Petkovic, M., Etalle, S. & Pechenizkiy, M., 1 Feb 2017, In : Journal of Information Security and Applications. 32, p. 27-46 20 p.

Research output: Contribution to journalArticleAcademicpeer-review

16 Citations (Scopus)
9 Downloads (Pure)
2018

A bounded-size clustering algorithm on fully-dynamic streaming graphs

Zhang, J., Pei, Y., Fletcher, G. & Pechenizkiy, M., 1 Sep 2018, In : Intelligent Data Analysis. 22, 5, p. 1039-1058 20 p.

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Apriori versions based on MapReduce for mining frequent patterns on big data

Luna, J. M., Padillo, F., Pechenizkiy, M. & Ventura, S., Oct 2018, In : IEEE Transactions on Cybernetics. 48, 10, p. 2851-2865 15 p., 8052219.

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Scopus)

Assessment of visibility graph similarity as a synchronization measure for chaotic, noisy and stochastic time series

Ahmadi, N., Besseling, R. M. H. & Pechenizkiy, M., 1 Dec 2018, In : Social Network Analysis and Mining. 8, 1, 17 p., 47.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access
File
3 Citations (Scopus)
96 Downloads (Pure)

Mining context-aware association rules using grammar-based genetic programming

Luna, J. M., Pechenizkiy, M., del Jesus, M. J. & Ventura, S., 1 Nov 2018, In : IEEE Transactions on Cybernetics. 48, 11, p. 3030-3044 15 p., 8049471.

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)

Twitter rumour detection in the health domain

Sicilia, R., Lo Giudice, S., Pei, Y., Pechenizkiy, M. & Soda, P., 15 Nov 2018, In : Expert Systems with Applications. 110, p. 33-40 8 p.

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Scopus)
2019

Adversarial balancing-based representation learning for causal effect inference with observational data

Du, X., Sun, L., Duivesteijn, W., Nikolaev, A. & Pechenizkiy, M., 30 Apr 2019, In : arXiv. 17 p., 1904.13335v1.

Research output: Contribution to journalArticleAcademic

40 Downloads (Pure)

Cluster-preserving sampling from fully-dynamic streaming graphs

Zhang, J., Zhu, K., Pei, Y., Fletcher, G. & Pechenizkiy, M., 1 May 2019, In : Information Sciences. 482, p. 279-300 22 p.

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
3 Downloads (Pure)

Effect of linear mixing in EEG on synchronization and complex network measures studied using the Kuramoto model

Ahmadi, N., Pei, Y. & Pechenizkiy, M., 15 Apr 2019, In : Physica A: Statistical Mechanics and its Applications. 520, p. 289-308 20 p.

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)
1 Downloads (Pure)

Evolving plasticity for autonomous learning under changing environmental conditions

Yaman, A., Mocanu, D., Iacca, G., Coler, M., Fletcher, G. & Pechenizkiy, M., 2019, In : arXiv. 26 p., 1904.01709v1.

Research output: Contribution to journalArticleAcademic

Open Access
File
18 Downloads (Pure)

Intrinsically sparse long short-term memory networks

Liu, S., Mocanu, D. & Pechenizkiy, M., 26 Jan 2019, In : arXiv. 9 p., 1901.09208v1.

Research output: Contribution to journalArticleAcademic

Open Access
File
26 Downloads (Pure)
2020

Bridging learning sciences, machine learning and affective computing for understanding cognition and affect in collaborative learning

Järvelä, S., Gašević, D., Seppänen, T., Pechenizkiy, M. & Kirschner, P. A., 1 Jan 2020, (Accepted/In press) In : British Journal of Educational Technology.

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)

Controlling the accuracy and uncertainty trade-off in RUL prediction with a surrogate Wiener propagation model

Deng, Y., Bucchianico, A. D. & Pechenizkiy, M., Apr 2020, In : Reliability Engineering and System Safety. 196, 10 p., 106727.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access
3 Citations (Scopus)

EEG-based classification of epilepsy and PNES: EEG microstate and functional brain network features

Ahmadi, N., Pei, Y., Carrette, E., Aldenkamp, A. P. & Pechenizkiy, M., 1 Dec 2020, In : Brain Informatics. 7, 1, 22 p., 6.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access

Ensuring cybersecurity of smart grid against data integrity attacks under concept drift

Mohammadpourfard, M., Weng, Y., Pechenizkiy, M., Tajdinian, M. & Mohammadi-Ivatloo, B., Jul 2020, In : International Journal of Electrical Power and Energy Systems. 119, 9 p., 105947.

Research output: Contribution to journalArticleAcademicpeer-review

2 Citations (Scopus)

Exceptional spatio-temporal behavior mining through Bayesian non-parametric modeling

Du, X., Pei, Y., Duivesteijn, W. & Pechenizkiy, M., 2020, (Accepted/In press) In : Data Mining and Knowledge Discovery.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access

Knowledge Elicitation using Deep Metric Learning and Psychometric Testing

Yin, L., Menkovski, V. & Pechenizkiy, M., 14 Apr 2020, In : arXiv.

Research output: Contribution to journalArticleAcademic

File
1 Downloads (Pure)

Sparse evolutionary deep learning with over one million artificial neurons on commodity hardware

Liu, S., Mocanu, D., Ramapuram Matavalam, A. R., Pei, Y. & Pechenizkiy, M., 6 Jul 2020, In : Neural Computing and Applications. 16 p.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access
16 Downloads (Pure)

struc2gauss: Structural role preserving network embedding via Gaussian embedding

Pei, Y., Du, X., Zhang, J., Fletcher, G. & Pechenizkiy, M., 1 Jul 2020, In : Data Mining and Knowledge Discovery. 34, 4, p. 1072–1103 32 p.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access