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https://r.donnu.edu.ua/handle/123456789/2861
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DC Field | Value | Language |
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dc.contributor.author | Половенко, Людмила Петрівна | - |
dc.contributor.author | Мерінова, Світлана Володимирівна | - |
dc.date.accessioned | 2023-05-15T09:04:57Z | - |
dc.date.available | 2023-05-15T09:04:57Z | - |
dc.date.issued | 2022 | - |
dc.identifier.other | УДК 004.777(045) | - |
dc.identifier.other | https://doi.org/10.52058/2708-7530-2022-5(23)-273-284 | - |
dc.identifier.uri | https://r.donnu.edu.ua/handle/123456789/2861 | - |
dc.description | Стаття у журналі "Наукові перспективи": 2022. No 5(22). С. 273-284 | en_US |
dc.description.abstract | The rapid increase in the size, volume, diversity and speed of geospatial data leads to the availability of spatial data infrastructures and compatible services, As a result we face the necessity of the knowledge extraction from bulk data. The production of knowledge by different intellectual analysis methods of distributed data in the spatial database remains a critical issue. The article presents the most common technologies of data mining. The authors review the process of knowledge discovery in databases and consider the data mining technologies as one of the component of this process. In the article we analyse the technologies of data mining as the basis of web mining technology. The categories of Web Mining: analysis of the use of web resources; extraction of web structures; web content extraction. The authors offer to examine the main mechanisms of research and extraction of information from webdocuments and services. In the article we substain the using of the web services of knowledge production as a layer over spatial data infrastructures as an effective methods to provide users with spatial data and decision making, the ability to extract knowledge from arrays of heterogeneous spatial data. One of the main emphasis of the article is the that the Hadoop and Spark frameworks provide high productivity of extracting templates and knowledge from large amounts of spatial data. Web services for extracting knowledge from real geodata allow us to use a dynamic, simpler and much faster procedure for producing knowledge from spatial data. | en_US |
dc.publisher | Міжнародна наукометрична база Index Copernicus (IC), | en_US |
dc.relation.ispartofseries | Наукові перспективи;No 5(22). С. 273-284 | - |
dc.subject | інтелектуальний аналіз даних | en_US |
dc.subject | продукування знань | en_US |
dc.subject | інтелектуальне розподілене середовище | en_US |
dc.subject | методи web-mining | en_US |
dc.subject | веб-сервіси видобування знань | en_US |
dc.subject | data mining | en_US |
dc.subject | knowledge production | en_US |
dc.subject | intelligent distributed | en_US |
dc.subject | environment | en_US |
dc.subject | Web-mining methods | en_US |
dc.subject | web services for knowledge extraction | en_US |
dc.title | ТЕХНОЛОГІЇ ПРОДУКУВАННЯ ЗНАНЬ НА ОСНОВІ ВЕБ-СЕРВІСІВ | en_US |
dc.title.alternative | KNOWLEDGE PRODUCTION TECHNOLOGIES WITH THE HELP OF WEB SERVICES | en_US |
dc.type | Article | en_US |
Appears in Collections: | Бібліографічні матеріали |
Files in This Item:
File | Description | Size | Format | |
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ТЕХНОЛОГІЇ ПРОДУКУВАННЯ ЗНАНЬ.pdf | Стаття у журналі "Наукові перспективи": 2022. No 5(22). С. 273-284 | 589,91 kB | Adobe PDF | View/Open |
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