Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics

Springer, 2020.

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Network Analysis Methodology of Policy Actors Identification and Power Evaluation (the case of the Unified State Exam introduction in Russia)

Зайцев Д. Г., Gregory Khvatsky, Таловский Н. И. и др., , in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics.: Springer, 2020. P. 231–244.

Добавлено: 7 ноября 2019 г.

GSM: Inductive Learning on Dynamic Graph Embeddings

Ананьева М. Е., Макаров И. А., Pendiukhov M., , in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics.: Springer, 2020. P. 85–99.

In this paper, we study the problem of learning graph embeddings for dynamic networks and the ability to generalize to unseen nodes called inductive learning. Firstly, we overview the state-of-the-art methods and techniques for constructing graph embeddings and learning algorithms for both transductive and inductive approaches. Secondly, we propose an improved GSM based on GraphSAGE ...

Добавлено: 27 февраля 2020 г.

Collaborator Recommender System

Anna Averchenkova, Alina Akhmetzyanova, Судариков К. В. и др., , in: Network Algorithms, Data Mining, and Applications. Springer Proceedings in Mathematics & Statistics.: Springer, 2020. P. 101–119.

Nowadays, a lot of scientists’ works aim to improve the quality of people’s life but it could be quite complicated without building a successful collaboration. Productive partnerships can increase research efficiency in many cases and make a huge impact on society. However, today there is no clear way to find such collaborators. In this paper, ...

Добавлено: 27 февраля 2020 г.