System Rekomendacyjny Item-based Collaborative Filtering

dc.contributor.author	Do, Thi Thu Trang
dc.date.accessioned	2021-08-19T09:08:09Z
dc.date.available	2021-08-19T09:08:09Z
dc.date.issued	2021-08-19
dc.identifier.issn	2021/I/D/6
dc.identifier.uri	https://repin.pjwstk.edu.pl/xmlui/handle/186319/823
dc.description.abstract	With the advance of technologies, there are numerous movies produced annually, which leads to information overload for the audience. Recommender was designed to overcome that issue and personalize the audience experience. This paper describes Item-based Collaborative Filtering Recommender, and reveals how the model predicts movie ratings on MovieLens data set. As shown at the end of this paper, the model outperforms the other movie recommender models.	pl_PL
dc.language.iso	en	pl_PL
dc.relation.ispartofseries	;Nr 6009
dc.subject	Artifcial Intelligence	pl_PL
dc.subject	Recommender	pl_PL
dc.subject	Predicting Ratings	pl_PL
dc.title	System Rekomendacyjny Item-based Collaborative Filtering	pl_PL
dc.title.alternative	Item-based Collaborative Filtering Recommender	pl_PL
dc.type	Thesis	pl_PL