?
A Method for Community Detection in Networks with Mixed Scale Features at its Nodes
P. 3–14.
Mirkin B., Shalileh S., Journal of Classification 2022 Vol. 39 P. 432–462
The problem of community detection in a network with features at its nodes takes into account both the graph structure and node features. The goal is to find relatively dense groups of interconnected entities sharing some features in common. There have been several approaches proposed for that. We apply the so-called data recovery approach to ...
Added: August 1, 2022
Artemova E., Maksimenko A., Охрименко Д. А., Социология: методология, методы, математическое моделирование 2021 № 52 С. 131–157
The paper attempts to classify the corruption-related media content of Russianlanguage and English-language Internet media using machine learning methods. The methodological approach proposed in the article is very relevant and promising, since, according to our earlier data, corruption monitoring mechanisms used in foreign publications based on the use of advanced information technologies have rather limited ...
Added: March 23, 2022
Ozcan S., Sakar O., Suloglu M., IEEE Transactions on Engineering Management 2021 Vol. 68 No. 5 P. 1372–1387
The amount of job advertisement data is rapidly growing, and this rich dataset is expected to have implications for the employment market, sector trajectories, and the education sector. Most significantly, human resources (HR) data has never previously been examined with the lens of tech mining for science and technology analyses. This article is the first ...
Added: December 12, 2021
IEEE, 2020.
Dimensionality reduction problem is stated as finding a mapping f:X ∈ R m → Z ∈ R n , where ≪ m while preserving some relevant properties of the data. We formulate topology-preserving dimensionality reduction as finding the optimal orthogonal projection to the lower-dimensional subspace which minimizes discrepancy between persistent diagrams of the original data and the projection. This ...
Added: October 14, 2021
Shalileh S., Mirkin B., Social Network Analysis and Mining 2021 Vol. 11 No. 1 P. 1–23
A feature-rich network is a network whose nodes are characterized by categorical or quantitative features. We propose a data-driven model for finding a partition of the nodes to approximate both the network link data and the feature data. The model involves summary quantitative characteristics of both network links and features. We distinguish between two modes ...
Added: July 29, 2021
Shalileh S., Mirkin B., Plos One 2021 Vol. 16 No. 7 Article 0254377
We explore a doubly-greedy approach to the issue of community detection in feature-rich networks. According to this approach, both the network and feature data are straightfor- wardly recovered from the underlying unknown non-overlapping communities, supplied with a center in the feature space and intensity weight(s) over the network each. Our least- squares additive criterion allows ...
Added: July 22, 2021
Tikhomirova K., Makarov I., , in: Analysis of Images, Social Networks and Texts: 9th International Conference, AIST 2020, Skolkovo, Moscow, Russia, October 15–16, 2020, Revised Selected PapersVol. 12602.: Springer, 2021. P. 294–302.
The paper studies the community detection problem on Telegram channels. The dataset is received from TGStat service and includes the information of 58k forwards between 100 politician Telegram channels. We implement modern clustering approaches to solve the problem of missing social links. Our study is based on a combination of structural features with strategy-based attributes, ...
Added: April 9, 2021
Zarodnyuk A., Trofimova E., Solovyov A. et al., Journal of Physics: Conference Series 2021 No. 1740 Article 012017
In the present work, we introduce a machine learning-based approach for galaxy clustering. It requires to determine clusters to provide further galaxies groups' masses estimation. The knowledge of mass distribution is crucial in dark matter research and study of the large-scale structure of the Universe. State-of-the-art telescopes allow various spectroscopy range data accumulation that highlights ...
Added: January 25, 2021
Shalileh S., Mirkin B., , in: Proceedings of MARAMI 2020 - Modèles & Analyse des Réseaux : Approches Mathématiques & Informatiques - The 11th Conference on Network Modeling and Analysis(Vol-2750)Vol. Vol-2750: Modèles & Analyse des Réseaux : Approches Mathématiques & Informatiques - Network Modeling and Analysis 2020.: CEUR-WS.org, 2020. P. 1–12.
The problem of community detection in a network with features at its nodes takes into account both the graph structure and node features. The goal is to find relatively dense groups of interconnected entities sharing some features in common. Existing approaches require the number of communities pre-specified. We apply the so-called data recovery approach to ...
Added: January 13, 2021
Shalileh S., Mirkin B., , in: Complex Networks & Their Applications IX. Volume 1: Proceedings of the Ninth International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2020.: Springer, 2021. P. 3–14.
The problem of community detection in a network with features at its nodes takes into account both the graph structure and node features. The goal is to find relatively dense groups of interconnected entities sharing some features in common. Algorithms based on probabilistic community models require the node features to be categorical. We use a ...
Added: January 13, 2021
Shalileh S., Mirkin B., , in: 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM).: Association for Computing Machinery (ACM), 2020. P. 99–104.
The problem of community detection in a network with features at its nodes takes into account both the graph structure and node features. The goal is to find relatively dense groups of interconnected entities sharing some features in common. We apply the so-called data recovery approach to the problem by combining the least-squares recovery criteria ...
Added: December 11, 2020
Scherbakova A., / NRU HSE. Series WP BRP "Linguistics". 2020.
Added: December 2, 2020
CEUR-WS.org, 2020.
MARAMI 2020
Modèles & Analyse des Réseaux : Approches Mathématiques & Informatiques - Network Modeling and Analysis 2020
Proceedings of MARAMI 2020 - Modèles & Analyse des Réseaux : Approches Mathématiques & Informatiques - The 11th Conference on Network Modeling and Analysis
Virtual Conference, October 14-15, 2020.
Edited by
Roberto Interdonato
CIRAD, UMR Tetis, Montpellier, France
TETIS, Univ. Montpellier, AgroParisTech, CIRAD, ...
Added: November 29, 2020
Shalileh S., Mirkin B., , in: Intelligent Data Engineering and Automated Learning – IDEAL 2020/ 21st International Conference, Guimaraes, Portugal, November 4–6, 2020, Proceedings, Part IIVol. 12490: Lecture Notes in Computer Science.: Cham: Springer, 2020. P. 413–422.
The problem of community detection in a network with features at its nodes takes into account both the graph structure and node features. The goal is to find relatively dense groups of interconnected entities sharing some features in common. We apply the so-called data recovery approach to the problem by combining the least-squares recovery criteria ...
Added: November 14, 2020