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...

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Bibliographic Details
Main Authors: Anna I. Guseva, Vasiliy S. Kireev, Stanislav A. Filippov
Format: Article
Language:English
Published: EconJournals 2016-12-01
Series:International Journal of Economics and Financial Issues
Online Access:https://www.econjournals.com/index.php/ijefi/article/view/3736
Description
Summary: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
ISSN:2146-4138