85 citations · 254 across the 14 of their papers we have counts for
17 papers
Generating Synthetic Citation Networks with Communities
Łukasz Brzozowski, Marek Gagolewski, Grzegorz Siudem
Generating realistic synthetic citation, patent, or component dependency networks is essential for benchmarking community detection, graph visualisation, and network data mining al…
Lumbermark: Resistant Clustering by Chopping Up Mutual Reachability Minimum Spanning Trees
Marek Gagolewski
We introduce Lumbermark, a robust divisive clustering algorithm capable of detecting clusters of varying sizes, densities, and shapes. Lumbermark iteratively chops off large limbs…
The Price-Pareto growth model of networks with community structure
Łukasz Brzozowski, Marek Gagolewski, Grzegorz Siudem +1
We introduce a new analytical framework for modelling degree sequences in individual communities of real-world networks, e.g., citations to papers in different fields. Our work is…
Gini-stable Lorenz curves and their relation to the generalised Pareto distribution
Lucio Bertoli-Barsotti, Marek Gagolewski, Grzegorz Siudem +1
We introduce an iterative discrete information production process where we can extend ordered normalised vectors by new elements based on a simple affine transformation, while pres…
Equivalence of inequality indices in the three-dimensional model of informetric impact
Lucio Bertoli-Barsotti, Marek Gagolewski, Grzegorz Siudem +1
Inequality is an inherent part of our lives: we see it in the distribution of incomes, talents, citations, to name a few. However, its intensity varies across environments: there a…
Community detection in complex networks via node similarity, graph representation learning, and hierarchical clustering
Łukasz Brzozowski, Grzegorz Siudem, Marek Gagolewski
Community detection is a critical challenge in analysing real graphs, including social, transportation, citation, cybersecurity, and many other networks. This article proposes thre…
Hierarchical clustering with OWA-based linkages, the Lance-Williams formula, and dendrogram inversions
Marek Gagolewski, Anna Cena, Simon James +1
Agglomerative hierarchical clustering based on Ordered Weighted Averaging (OWA) operators not only generalises the single, complete, and average linkages, but also includes intercl…
Clustering with minimum spanning trees: How good can it be?
Marek Gagolewski, Anna Cena, Maciej Bartoszuk +1
Minimum spanning trees (MSTs) provide a convenient representation of datasets in numerous pattern recognition activities. Moreover, they are relatively fast to compute. In this pap…
Deep R Programming
Marek Gagolewski
Deep R Programming is a comprehensive and in-depth introductory course on one of the most popular languages for data science. It equips ambitious students, professionals, and resea…
Minimalist Data Wrangling with Python
Marek Gagolewski
Minimalist Data Wrangling with Python is envisaged as a student's first introduction to data science, providing a high-level overview as well as discussing key concepts in detail.…
Genie: A new, fast, and outlier-resistant hierarchical clustering algorithm
Marek Gagolewski, Maciej Bartoszuk, Anna Cena
The time needed to apply a hierarchical clustering algorithm is most often dominated by the number of computations of a pairwise dissimilarity measure. Such a constraint, for large…
A framework for benchmarking clustering algorithms
Marek Gagolewski
The evaluation of clustering algorithms can involve running them on a variety of benchmark problems, and comparing their outputs to the reference, ground-truth groupings provided b…
Normalised clustering accuracy: An asymmetric external cluster validity measure
Marek Gagolewski
There is no, nor will there ever be, single best clustering algorithm. Nevertheless, we would still like to be able to distinguish between methods that work well on certain task ty…
Data Fusion: Theory, Methods, and Applications
Marek Gagolewski
A proper fusion of complex data is of interest to many researchers in diverse fields, including computational statistics, computational geometry, bioinformatics, machine learning,…
Are Cluster Validity Measures (In)valid?
Marek Gagolewski, Maciej Bartoszuk, Anna Cena
Internal cluster validity measures (such as the Calinski-Harabasz, Dunn, or Davies-Bouldin indices) are frequently used for selecting the appropriate number of partitions a dataset…
Power Laws, the Price Model, and the Pareto type-2 Distribution
Grzegorz Siudem, Przemysław Nowak, Marek Gagolewski
We consider a version of D. Price's model for the growth of a bibliographic network, where in each iteration a constant number of citations is randomly allocated according to a wei…
Agent-based model for the h-index - Exact solution
Barbara Żogała-Siudem, Grzegorz Siudem, Anna Cena +1
The Hirsch's -index is perhaps the most popular citation-based measure of the scientific excellence. In 2013 G. Ionescu and B. Chopard proposed an agent-based model for this ind…