Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Oksana Severiukhina"'
Autor:
Oksana Severiukhina, Sergey Kesarev, Klavdiya Bochenina, Alexander Boukhanovsky, Michael H. Lees, Peter M. A. Sloot
Publikováno v:
Journal of Big Data, Vol 7, Iss 1, Pp 1-17 (2020)
Abstract This research proposes a system based on a combination of various components for parallel modelling and forecasting the processes in networks with data assimilation from the real network. The main novelty of this work consists of the assimil
Externí odkaz:
https://doaj.org/article/95c13b7d0e3444799fa0c2396c7ee535
A trust and relevance-based Point-Of-Interest recommendations method with inaccessible user location
Publikováno v:
In Procedia Computer Science 2020 178:153-161
Publikováno v:
Procedia Computer Science. 156:274-282
The paper presents an unsupervised method for anomaly detection named Adaptive Suppression (AS). The method relies on distance metrics between data points and receives hypothesis about percent of anomalies in dataset. Data points having initial accum
Autor:
Michael Lees, Oksana Severiukhina, Sergey Kesarev, Alexander V. Boukhanovsky, Klavdiya Bochenina, Peter M. A. Sloot
Publikováno v:
Journal of Big Data, Vol 7, Iss 1, Pp 1-17 (2020)
Journal of Big Data, 7:72. Springer Open
Journal of Big Data, 7:72. Springer Open
This research proposes a system based on a combination of various components for parallel modelling and forecasting the processes in networks with data assimilation from the real network. The main novelty of this work consists of the assimilation of
Publikováno v:
Procedia Computer Science. 136:228-235
Nowadays, social networks have become one of the main sources of information. There are many factors affecting the information spreading. On the one hand, we must take into account the features of post and information sources, on the other hand, it i
Publikováno v:
Procedia Computer Science. 136:218-227
When large complex networks are under consideration, one needs to exploit parallel computations to be able to get the result of simulation in time. To maintain the efficiency of calculations, different graph partitioning and dynamic load balancing al
Publikováno v:
ICCS
Procedia Computer Science, 108, 215-224. Elsevier
Procedia Computer Science, 108, 215-224. Elsevier
This paper presents the research on the influence of obstacles on crowd dynamics. We have performed experiments for four base scenarios of interaction in crowd: unidirectional flow, bidirectional flow, merging flows and intersection. Movement of pede
Publikováno v:
Procedia Computer Science. 119:139-146
Simulation of the agent-based model has several problems related to scalability, the accuracy of reproduction of motion. The increase in the number of agents leads to additional computations and hence the program run time also increases. This problem
Publikováno v:
SNAMS
Users on the social network have both different levels of involvement and preferred topics. In this paper, we try to understand how the behavior of users in different activity segments varies and how predictable the behavior of segments is. To identi
Publikováno v:
SNAMS
We propose the clustering-based approach for customer segmentation based on their digital traces. The weighted graph of co-occurrences of interests is created (with and without an account of socio-demographical stratum), and the graph is further clus