10 citations · 20 across the 10 of their papers we have counts for
18 papers
Using synthetic networks for parameter tuning in community detection
Liudmila Prokhorenkova
Community detection is one of the most important and challenging problems in network analysis. However, real-world networks may have very different structural properties and commun…
Clustering Properties of Spatial Preferential Attachment Model
Lenar Iskhakov, Bogumil Kaminski, Maksim Mironov +2
In this paper, we study the clustering properties of the Spatial Preferential Attachment (SPA) model introduced by Aiello et al. in 2009. This model naturally combines geometry and…
Community Detection through Likelihood Optimization: In Search of a Sound Model
Liudmila Prokhorenkova, Alexey Tikhonov
Community detection is one of the most important problems in network analysis. Among many algorithms proposed for this task, methods based on statistical inference are of particula…
Preferential placement for community structure formation
Aleksandr Dorodnykh, Liudmila Ostroumova Prokhorenkova, Egor Samosvat
Various models have been recently proposed to reflect and predict different properties of complex networks. However, the community structure, which is one of the most important pro…
PageRank in Undirected Random Graphs
Konstantin Avrachenkov, Arun Kadavankandy, Liudmila Ostroumova Prokhorenkova +1
PageRank has numerous applications in information retrieval, reputation systems, machine learning, and graph partitioning. In this paper, we study PageRank in undirected random gra…
Modularity of complex networks models
Liudmila Ostroumova Prokhorenkova, Pawel Pralat, Andrei Raigorodskii
Modularity is designed to measure the strength of division of a network into clusters (known also as communities). Networks with high modularity have dense connections between the…
Assortativity in Generalized Preferential Attachment Models
Alexander Krot, Liudmila Ostroumova Prokhorenkova
In this paper, we analyze assortativity of preferential attachment models. We deal with a wide class of preferential attachment models (PA-class). It was previously shown that the…
PageRank in undirected random graphs
Konstantin Avrachenkov, Arun Kadavankandy, Liudmila Ostroumova +1
PageRank has numerous applications in information retrieval, reputation systems, machine learning, and graph partitioning.In this paper, we study PageRank in undirected random grap…
Local Clustering Coefficient in Generalized Preferential Attachment Models
Alexander Krot, Liudmila Ostroumova Prokhorenkova
In this paper, we analyze the local clustering coefficient of preferential attachment models. A general approach to preferential attachment was introduced in earlier, where a wide…
Global clustering coefficient in scale-free weighted and unweighted networks
Liudmila Ostroumova Prokhorenkova
In this paper, we present a detailed analysis of the global clustering coefficient in scale-free graphs. Many observed real-world networks of diverse nature have a power-law degree…
Global clustering coefficient in scale-free networks
Liudmila Ostroumova Prokhorenkova, Egor Samosvat
In this paper, we analyze the behavior of the global clustering coefficient in scale free graphs. We are especially interested in the case of degree distribution with an infinite v…
Recency-based preferential attachment models
Liudmila Ostroumova Prokhorenkova, Egor Samosvat
Preferential attachment models were shown to be very effective in predicting such important properties of real-world networks as the power-law degree distribution, small diameter,…
Timely crawling of high-quality ephemeral new content
Damien Lefortier, Liudmila Ostroumova, Egor Samosvat +1
Nowadays, more and more people use the Web as their primary source of up-to-date information. In this context, fast crawling and indexing of newly created Web pages has become cruc…
The distribution of second degrees in the Buckley-Osthus random graph model
Andrey Kupavskii, Liudmila Ostroumova, Dmitriy Shabanov +1
In this paper we consider a well-known generalization of the Barabási and Albert preferential attachment model - the Buckley-Osthus model. Buckley and Osthus proved that in this mo…
Evolution of the Media Web
Damien Lefortier, Liudmila Ostroumova, Egor Samosvat
We present a detailed study of the part of the Web related to media content, i.e., the Media Web. Using publicly available data, we analyze the evolution of incoming and outgoing l…
Empirical Validation of the Buckley--Osthus Model for the Web Host Graph: Degree and Edge Distributions
Maxim Zhukovskiy, Dmitry Vinogradov, Yuri Pritykin +5
There has been a lot of research on random graph models for large real-world networks such as those formed by hyperlinks between web pages in the world wide web. Though largely suc…
Generalized preferential attachment: tunable power-law degree distribution and clustering coefficient
Liudmila Ostroumova, Alexander Ryabchenko, Egor Samosvat
We propose a wide class of preferential attachment models of random graphs, generalizing previous approaches. Graphs described by these models obey the power-law degree distributio…
The distribution of second degrees in the Bollobás--Riordan random graph model
Liudmila Ostroumova, Evgeniy Grechnikov
We prove that the distribution of second degrees in the Bollobás--Riordan random graph model obeys the power law. We consider the model with parameter m = 1 (the number of edges eq…