Highly Pertinent Algorithm for the Market of Business Intelligence, Context and Native Advertising

Autor:	GUSEVA, Anna İ., KİREEV, Vasiliy S., FİLİPPOV, Stanislav A.
Jazyk:	angličtina
Rok vydání:	2016
Předmět:	highly pertinent algorithms lcsh:HB71-74 context and native advertising market lcsh:Economics as a science context and native advertising market Business Intelligence market highly pertinent algorithms recommender systems recommender systems lcsh:Business business intelligence market lcsh:HF5001-6182
Zdroj:	International Journal of Economics and Financial Issues, Vol 6, Iss 8, Pp 225-233 (2016) Volume: 6, Issue: 8 225-233 International Journal of Economics and Financial Issues
ISSN:	2146-4138
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::119cc17326da22445277708c876b5c1b https://dergipark.org.tr/tr/pub/ijefi/issue/32018/354106?publisher=http-www-cag-edu-tr-ilhan-ozturk Zobrazit plný text záznamu