Вісники НТУ "ХПІ"

Постійне посилання на розділhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/2494


З 1961 р. у ХПІ видається збірник наукових праць "Вісник Харківського політехнічного інституту".
Згідно до наказу ректора № 158-1 від 07.05.2001 року "Про упорядкування видання вісника НТУ "ХПІ", збірник був перейменований у Вісник Національного Технічного Університету "ХПІ".
Вісник Національного технічного університету "Харківський політехнічний інститут" включено до переліку спеціалізованих видань ВАК України і виходить по серіях, що відображають наукові напрямки діяльності вчених університету та потенційних здобувачів вчених ступенів та звань.
Зараз налічується 30 діючих тематичних редколегій. Вісник друкує статті як співробітників НТУ "ХПІ", так і статті авторів інших наукових закладів України та зарубіжжя, які представлені у даному розділі.

Переглянути

Фільтри

2021 - 20222

Налаштування

ORCID: search.filters.orcid.https://orcid.org/0000-0001-5448-2488Ключові слова: search.filters.subject.ключове слово

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Зараз показуємо 1 - 2 з 2
  • Ескіз
    Документ
    Problem of classification of semantic kernels of web resource
    (Національний технічний університет "Харківський політехнічний інститут", 2022) Orekhov, Sergey Valerievich; Malyhon, Hennadiy Vasilievich; Stratiienko, Nataliia Kostiantunivna
    The article presents a new theoretical basis for solving the problem of situational management of semantic cores identified on the basis of WEB content. Such a task arises within the framework of a new phenomenon called virtual promotion. Its essence lies in the fact that a real product can exist in two realities: online and offline. According to marketing theory, the lifetime in two realities is the same. However, in the online mode, the goods exist independently and in accordance with the laws of the use of Internet technologies. Therefore, based on the concept of a marketing channel, it was proposed to consider a message in such a channel as a semantic core. The core is a specially selected set of keywords that briefly describe the product and the corresponding need. It has been proposed that each need forms a so-called class of need. Therefore, the product description will either belong to this class or not. In addition, a product can be described by a different set of keywords, which means that different descriptions of the same product or several products, if there are any for sale in the enterprise, will fall into the demand class. As a result, in this work, it was proposed to consider the center of this class as the so-called K-candidate. It is the K-applicant that will be the semantic core that will be considered at the current iteration of the situational management process. In addition, in order to move from one situation to another, in other words, from one core to another, it is required to have such an alternative core. It can be safely taken either from the neighborhood of the need class center (K-applicant), or the center of another class (another K-applicant), if the product can cover several needs of a potential buyer. Then the actual task is to classify the classes of needs based on the text corpus in HTML format. Having a text corpus at the first stage, the task of synthesizing semantic cores is realized, and then the classification task itself. This article proposes the formulation of the classification problem, taking into account the features that the Internet technologies contribute to search engine optimization. In particular, it is proposed to use four metrics from the category of WEB statistics. And then it is proposed to use the clustering method to identify classes of needs, taking into account the fact that the K-applicant is presented as a semantic network or as a graph.
  • Ескіз
    Документ
    Modelling semantic kernel of web resource
    (Національний технічний університет "Харківський політехнічний інститут", 2021) Orekhov, Sergey Valerievich; Malyhon, Hennadiy Vasilievich
    The article presents an attempt to describe mathematically the effect of the semantic kernel of a web resource on the Internet. In accordance with the theory of marketing, the product that we want to sell on the network is characterized by the following basic properties: price, time and place. In other words, a potential buyer wants to receive a given product in the right place at a given time. To satisfy this need, it is necessary to use the classic component of marketing, product promotion. However, this component is now becoming a fully virtual instrument. This tool functions in a hypertext, video and image environment. Therefore, the user analyzes the meaning of these elements in order to get the desired product. The results of web projects carried out in this area indicate the emergence of a new phenomenon, which reflects the main meaning of virtual promotion – this is the semantic core. The core is a short annotation of the main properties of the product, its location and time of appearance. Therefore, the purpose of this article is both a presentation of a new object of research and a mathematical description. It is assumed that the semantic core is formed on the basis of natural language terms. In other words, the semantic core is a set of keywords that are grouped by meaning. We propose to use data mining approaches for clustering to group terms. The classic clustering method at the moment is k-means. The article presents a model of the semantic core based on this method. This method and its distance function are considered as the second stage of web content processing. At the first stage, web content is converted into a semantic web. However, the k-means technique has significant drawbacks when modeling the semantic core. Therefore, in the development of this idea, the work shows an alternative way to modeling the kernel. As an alternative approach, the construction of clusters based on the concept of maximum flow is considered. This approach has the significant advantage that the type of links in the semantic network overlaps with the type of distance function in this method. As a result, on a real web project, the effect of the connection between the semantic core model and the level of new users of the web resource was demonstrated over the past five years.