Highly Pertinent Algorithm for the Market of Business Intelligence, Context and Native Advertising
This article presents the study results of the business intelligence markets, the promote products on social media, and a new method for increasing the information pertinence in the scientific recommender systems, scientific information systems, analysis of the recommender systems that contain info...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
EconJournals
2016-12-01
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Series: | International Journal of Economics and Financial Issues |
Online Access: | https://www.econjournals.com/index.php/ijefi/article/view/3736 |
_version_ | 1797918322190188544 |
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author | Anna I. Guseva Vasiliy S. Kireev Stanislav A. Filippov |
author_facet | Anna I. Guseva Vasiliy S. Kireev Stanislav A. Filippov |
author_sort | Anna I. Guseva |
collection | DOAJ |
description |
This article presents the study results of the business intelligence markets, the promote products on social media, and a new method for increasing the information pertinence in the scientific recommender systems, scientific information systems, analysis of the recommender systems that contain information about scientific publications, is represented. The prospects of using this method in the Business Intelligence systems, content management systems for native advertising systems to find content on the Internet and assessed the current state of the market such systems.
Keywords: context and native advertising market, Business Intelligence market, highly pertinent algorithms, recommender systems
JEL Classifications: A11, M30, M37
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first_indexed | 2024-04-10T13:27:34Z |
format | Article |
id | doaj.art-133408fb76ed4855b2a76666cf05ef9f |
institution | Directory Open Access Journal |
issn | 2146-4138 |
language | English |
last_indexed | 2024-04-10T13:27:34Z |
publishDate | 2016-12-01 |
publisher | EconJournals |
record_format | Article |
series | International Journal of Economics and Financial Issues |
spelling | doaj.art-133408fb76ed4855b2a76666cf05ef9f2023-02-15T16:11:47ZengEconJournalsInternational Journal of Economics and Financial Issues2146-41382016-12-0168SHighly Pertinent Algorithm for the Market of Business Intelligence, Context and Native AdvertisingAnna I. GusevaVasiliy S. KireevStanislav A. Filippov This article presents the study results of the business intelligence markets, the promote products on social media, and a new method for increasing the information pertinence in the scientific recommender systems, scientific information systems, analysis of the recommender systems that contain information about scientific publications, is represented. The prospects of using this method in the Business Intelligence systems, content management systems for native advertising systems to find content on the Internet and assessed the current state of the market such systems. Keywords: context and native advertising market, Business Intelligence market, highly pertinent algorithms, recommender systems JEL Classifications: A11, M30, M37 https://www.econjournals.com/index.php/ijefi/article/view/3736 |
spellingShingle | Anna I. Guseva Vasiliy S. Kireev Stanislav A. Filippov Highly Pertinent Algorithm for the Market of Business Intelligence, Context and Native Advertising International Journal of Economics and Financial Issues |
title | Highly Pertinent Algorithm for the Market of Business Intelligence, Context and Native Advertising |
title_full | Highly Pertinent Algorithm for the Market of Business Intelligence, Context and Native Advertising |
title_fullStr | Highly Pertinent Algorithm for the Market of Business Intelligence, Context and Native Advertising |
title_full_unstemmed | Highly Pertinent Algorithm for the Market of Business Intelligence, Context and Native Advertising |
title_short | Highly Pertinent Algorithm for the Market of Business Intelligence, Context and Native Advertising |
title_sort | highly pertinent algorithm for the market of business intelligence context and native advertising |
url | https://www.econjournals.com/index.php/ijefi/article/view/3736 |
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