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Dauren Ayazbayev, Andrey Bogdanchikov, Kamila Orynbekova and Iraklis Varlamis
This work focuses on determining semantically close words and using semantic similarity in general in order to improve performance in information retrieval tasks. The semantic similarity of words is an important task with many applications from informati...
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Kang-Ren Leow, Meng-Chew Leow and Lee-Yeng Ong
The Online Roadshow, a new type of web application, is a digital marketing approach that aims to maximize contactless business engagement. It leverages web computing to conduct interactive game sessions via the internet. As a result, massive amounts of p...
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Dohoon Lee, David Camacho and Jason J. Jung
Many vehicles are connected to the Internet, and big data are continually created. Various studies have been conducted involving the development of artificial intelligence, machine learning technology, and big data frameworks. The analysis of smart mobil...
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Jai Prakash Verma, Shir Bhargav, Madhuri Bhavsar, Pronaya Bhattacharya, Ali Bostani, Subrata Chowdhury, Julian Webber and Abolfazl Mehbodniya
The recent advancements in big data and natural language processing (NLP) have necessitated proficient text mining (TM) schemes that can interpret and analyze voluminous textual data. Text summarization (TS) acts as an essential pillar within recommendat...
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P.A Golovnyak,K.S. Zaytsev,A.M. Pinchuk
Pág. 94 - 101
Today there is a significant increase in the number of payments made using plastic cards. Banking organizations are forced to analyze huge amounts of data in their work, and therefore software products for processing big data are being put into operation...
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Jamil Al-Sawwa and Mohammad Almseidin
With the rapid development of internet technology, the amount of collected or generated data has increased exponentially. The sheer volume, complexity, and unbalanced nature of this data pose a challenge to the scientific community to extract meaningful ...
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D.E. Savitsky,M.E. Dunaev,K.S. Zaytsev
Pág. 70 - 76
The purpose of this work is to study methods for detecting anomalies in the processing of data streams in distributed streams in real time. To do this, the authors carried out a modification of the K-Means algorithm, called K-Means in real time, and carr...
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R.A. Elchenkov,M.E. Dunaev,K.S. Zaytsev
Pág. 62 - 69
The purpose of this work is to study methods for predicting the values of time series when processing streaming data in distributed systems in real time. To do this, the authors propose a modification of the autoregressive model with a given AR order by ...
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Tanmaya Mahapatra and Syeeda Nilofer Banoo
Machine Learning (ML) has gained prominence and has tremendous applications in fields like medicine, biology, geography and astrophysics, to name a few. Arguably, in such areas, it is used by domain experts, who are not necessarily skilled-programmers. T...
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S. V. Hayrapetyan,K.S. Zaytsev
Pág. 30 - 38
The purpose of this paper is to describe the developed method of detecting network covert timing channels, based on machine learning algorithms. Detection of network covert channels is an actual problem, since the latter can be used to leak confidential ...
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