Machine Learning as a method of adapting offers to the clients

Recommendation systems are class of information filter applications whose main goal is to provide personalized recommendations. The main goal of the research was to compare two ways of creating personalized recommendations. The recommendation system was built on the basis of a content-based cogniti...

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Bibliographic Details
Main Authors:	Jacek Bielecki, Oskar Ceglarski, Maria Skublewska-Paszkowska
Format:	Article
Language:	English
Published:	Lublin University of Technology 2019-12-01
Series:	Journal of Computer Sciences Institute
Subjects:	recommender system; collaborative filtering; cognitive filtering; machine learning
Online Access:	https://ph.pollub.pl/index.php/jcsi/article/view/1293

id	doaj-b8e66951654e4a739ad12f110a15401f
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spelling	doaj-b8e66951654e4a739ad12f110a15401f2020-11-25T03:57:30ZengLublin University of TechnologyJournal of Computer Sciences Institute2544-07642019-12-011310.35784/jcsi.1293Machine Learning as a method of adapting offers to the clientsJacek Bielecki0Oskar Ceglarski1Maria Skublewska-Paszkowska2Lublin University of TechnologyLublin University of TechnologyLublin University of Technology Recommendation systems are class of information filter applications whose main goal is to provide personalized recommendations. The main goal of the research was to compare two ways of creating personalized recommendations. The recommendation system was built on the basis of a content-based cognitive filtering method and on the basis of a collaborative filtering method based on user ratings. The conclusions of the research show the advantages and disadvantages of both methods. https://ph.pollub.pl/index.php/jcsi/article/view/1293recommender system; collaborative filtering; cognitive filtering; machine learning
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Jacek Bielecki Oskar Ceglarski Maria Skublewska-Paszkowska
spellingShingle	Jacek Bielecki Oskar Ceglarski Maria Skublewska-Paszkowska Machine Learning as a method of adapting offers to the clients Journal of Computer Sciences Institute recommender system; collaborative filtering; cognitive filtering; machine learning
author_facet	Jacek Bielecki Oskar Ceglarski Maria Skublewska-Paszkowska
author_sort	Jacek Bielecki
title	Machine Learning as a method of adapting offers to the clients
title_short	Machine Learning as a method of adapting offers to the clients
title_full	Machine Learning as a method of adapting offers to the clients
title_fullStr	Machine Learning as a method of adapting offers to the clients
title_full_unstemmed	Machine Learning as a method of adapting offers to the clients
title_sort	machine learning as a method of adapting offers to the clients
publisher	Lublin University of Technology
series	Journal of Computer Sciences Institute
issn	2544-0764
publishDate	2019-12-01
description	Recommendation systems are class of information filter applications whose main goal is to provide personalized recommendations. The main goal of the research was to compare two ways of creating personalized recommendations. The recommendation system was built on the basis of a content-based cognitive filtering method and on the basis of a collaborative filtering method based on user ratings. The conclusions of the research show the advantages and disadvantages of both methods.
topic	recommender system; collaborative filtering; cognitive filtering; machine learning
url	https://ph.pollub.pl/index.php/jcsi/article/view/1293
work_keys_str_mv	AT jacekbielecki machinelearningasamethodofadaptingofferstotheclients AT oskarceglarski machinelearningasamethodofadaptingofferstotheclients AT mariaskublewskapaszkowska machinelearningasamethodofadaptingofferstotheclients
_version_	1724460436984692736

Machine Learning as a method of adapting offers to the clients

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