Methods and approaches to the development of a automated analysis’s system of the changes’ dynamics in the area of forest plantations based on the methods of automatic pattern recognition

Kuz'menko, Aleksandr; Kondrashin, D. V.

doi:10.30987/2619-1512-2019-2019-4-230-240

Cited by 5 publications

(4 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…This is especially useful for solving a classification problem with unbalanced data, i.e. when the number of objects belonging to various classes is very different [12].…”

Section: Hmmocs-ii 2023mentioning

confidence: 99%

Developing a machine learning model for fake news detection

Filippov,

Sazonova,

Leonov

2024

ITM Web Conf.

View full text Add to dashboard Cite

The article is devoted to the problem of detecting fake news. This issue is relevant nowadays. Fake news paves the way for deceiving people and promoting ideologies. People who provide incorrect information benefit by earning money from the number of interactions with their publications. One of the typical tasks that arise in the process of identifying news is determining whether news belongs to one of two classes, namely the fake news or the real news. With the help of modern methods of machine learning and primary data processing, this problem is effectively solved.

show abstract

“…This is especially useful for solving a classification problem with unbalanced data, i.e. when the number of objects belonging to various classes is very different [12].…”

Section: Hmmocs-ii 2023mentioning

confidence: 99%

Developing a machine learning model for fake news detection

Filippov,

Sazonova,

Leonov

2024

ITM Web Conf.

View full text Add to dashboard Cite

show abstract

“…В результате будет получена гистограмма для сравнения тональностей ключевых слов одного уровня. Представленная математическая модель может быть использована при проектировании подобных систем информационного анализа [9][10][11][12][13][14][15][16][17].…”

Section: результаты исследований и их обсуждениеunclassified

Analysis of Customer Experience in the Hotel Business

Filippov¹,

Sazonova²,

Lazareva³

et al. 2022

Applied Mathematics and Control Sciences

View full text Add to dashboard Cite

In the process of marketing research, it is necessary to process large volumes of accumulated reviews, so it is obvious that the process of processing and analysis should be automated. Modern technical capabilities allow you to create an information and analytical system for formalized analysis of consumer reviews about hotels. The analysis of consumer reviews contributes to the development of the hotel business, since reviews are a qualitative way to assess the effectiveness of the company. With their help, it becomes clear what elements of the hotel complex should be paid attention to with the aim of their possible improvement in the future. The trends observed in reviews also allow you to find out what consumers expect and how best of all you can live up to their expectations. In fact, the task of analyzing the tonality of the text is equivalent to the problem of text classification, where tonal estimates can be categories of texts. To teach the classification model, a set of marked data downloaded from the Internet was used. The set contains 18,500 reviews about the hotels of Europe in Russian with the tonality indicated for them. The article is devoted to the urgent problem of determining the consumer attitude to services provided in the hotel business based on reviews from the Internet. A solution to the problem of analyzing the tonality of the entities of the hotel, extracted from the reviews about the hotel. To solve the problem, the MLP algorithm is selected, since the task of analyzing tonality is reduced to the task of classification, where tonal estimates are classification classes. Particular attention is paid to the algorithm for teaching a classification model developed using the Keras library in Python. To solve the task of analyzing the tonality of entit

show abstract

“…Data mining is the process of discovering previously unknown, non-trivial, practically useful and available to interpretation knowledge in raw data, which is necessary for making decisions in various human activities [2,13]. Data Mining methods were used to solve the following tasks: to determine the audience's reaction to the content, to define the target profile of subscribers, and to find the dependencies between user interests.…”

Section: Data Miningmentioning

confidence: 99%

Analysis of Social Networks Using an Information and Analytical System

et al. 2021

View full text Add to dashboard Cite

The subject of the study is the analysis of social networks and the construction of an information and analytical system to automate data monitoring and mining. Modern social network analysis systems are reviewed, and the distinguishing features of these systems are given. Various methods of social network analysis and tasks that can be solved using these methods are described. The effectiveness of the methods to determine the text sentiment is compared.

show abstract

Methods and approaches to the development of a automated analysis’s system of the changes’ dynamics in the area of forest plantations based on the methods of automatic pattern recognition

Cited by 5 publications

References 3 publications

Developing a machine learning model for fake news detection

Developing a machine learning model for fake news detection

Analysis of Customer Experience in the Hotel Business

Analysis of Social Networks Using an Information and Analytical System

Contact Info

Product

Resources

About