Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Kristina Machova"'
Publikováno v:
Sensors, Vol 22, Iss 1, p 155 (2021)
The article focuses on solving an important problem of detecting suspicious reviewers in online discussions on social networks. We have concentrated on a special type of suspicious authors, on trolls. We have used methods of machine learning for gene
Externí odkaz:
https://doaj.org/article/524bf7d5cbdf4da49c9770e10079f94a
Autor:
Kristina Machova
Publikováno v:
Journal of Information and Organizational Sciences, Vol 33, Iss 1 (2009)
The paper presents an approach to partial mapping of a web sub-graph. This sub-graph contains the nearest surroundings of an actual web page. Our work deals with acquiring relevant Hyperlinks of a base web site, generation of adjacency matrix, the ne
Externí odkaz:
https://doaj.org/article/d8d87fd93c5a44be922af8d2c2532fea
Publikováno v:
Journal of Information and Organizational Sciences, Vol 31, Iss 1 (2007)
The presented paper describes statistical methods (information gain, mutual X^2 statistics, and TF-IDF method) for key words generation from a text document collection. These key words should characterise the content of text documents and can be used
Externí odkaz:
https://doaj.org/article/ce43ae5254ce444d9de74437a96c3eaa
Publikováno v:
Sensors, Vol 24, Iss 11, p 3590 (2024)
This article explores the possibilities for federated learning with a deep learning method as a basic approach to train detection models for fake news recognition. Federated learning is the key issue in this research because this kind of learning mak
Externí odkaz:
https://doaj.org/article/32bf89e83d7747ec80c14396ef435e30
Publikováno v:
Frontiers in Psychology, Vol 14 (2023)
Emotions are an integral part of human life. We know many different definitions of emotions. They are most often defined as a complex pattern of reactions, and they could be confused with feelings or moods. They are the way in which individuals cope
Externí odkaz:
https://doaj.org/article/ca5bb0b5befa42a8840e98bee1375031
Publikováno v:
Sensors, Vol 22, Iss 23, p 9319 (2022)
This article focuses on the problem of detecting disinformation about COVID-19 in online discussions. As the Internet expands, so does the amount of content on it. In addition to content based on facts, a large amount of content is being manipulated,
Externí odkaz:
https://doaj.org/article/107425e75f8b4869b247fd9109039437
Publikováno v:
Sensors, Vol 22, Iss 17, p 6468 (2022)
This article focuses on the problem of detecting toxicity in online discussions. Toxicity is currently a serious problem when people are largely influenced by opinions on social networks. We offer a solution based on classification models using machi
Externí odkaz:
https://doaj.org/article/40f15ce4ac744a8ea91db36a02b6e1ec
Autor:
Martin MIKULA, Kristína MACHOVÁ
Publikováno v:
Acta Electrotechnica et Informatica, Vol 18, Iss 2, Pp 27-34 (2018)
Sentiment analysis in the minor languages, such as Slovak, using dictionary approach is a difficult task. It requires a lot of human effort and it is time-consuming to prepare a reliable source of information, especially good dictionary. We propose
Externí odkaz:
https://doaj.org/article/d727637f2b9240ec9a2215d073bcf1f0
Publikováno v:
Applied Sciences, Vol 10, Iss 23, p 8631 (2020)
The emergence of anti-social behaviour in online environments presents a serious issue in today’s society. Automatic detection and identification of such behaviour are becoming increasingly important. Modern machine learning and natural language pr
Externí odkaz:
https://doaj.org/article/a656b754a6e5466dad082d926d97d495