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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)

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)

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)

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)

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
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3 Citations (Scopus)
96 Downloads (Pure)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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)

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

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)

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)

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
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18 Downloads (Pure)

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

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

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)

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
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94 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)

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
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26 Downloads (Pure)

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
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48 Downloads (Pure)

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)

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)

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)

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)

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)

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)

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

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

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)

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)

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)

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)

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

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)

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

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)