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Record type:	stať ve sborníku (D)
Home Department:	Katedra informatiky a počítačů (31400)
Title:	Content-based recommender system for online stores using expert system
Citace	Walek, B. a Špačková, P. Content-based recommender system for online stores using expert system. In: The First IEEE International Conference on Artificial Intelligence and Knowledge Engineering (AIKE 2018): Proceedings of AIKE 2018 2018-09-26 Laguna Hills. IEEE, 2018. ISBN 978-153869555-5.

Subtitle
Publication year:	2018
Obor:
Number of pages:	2
Page from:	neuvedeno
Page to:	neuvedeno
Form of publication:	Elektronická verze
ISBN code:	978-153869555-5
ISSN code:
Proceedings title:	Proceedings of AIKE 2018
Proceedings:	Mezinárodní
Publisher name:	IEEE
Place of publishing:	neuvedeno
Country of Publication:	Sborník vydaný v zahraničí
Název konference:	The First IEEE International Conference on Artificial Intelligence and Knowledge Engineering (AIKE 2018)
Místo konání konference:	Laguna Hills
Datum zahájení konference:
Typ akce podle státní příslušnosti účastníků:	Celosvětová akce
WoS code:	000454624300027
EID:	2-s2.0-85058227775

Key words in English:	content-based system, recommender system, online store, expert system, adaptivity
Annotation in original language:	This paper deals with a content-based recommender system for online stores using the expert system. We propose an algorithm which adapts the content based on user preferences and the content viewed by the user. The main goal of the recommender system is to propose and deliver suitable content to the user. One of the goals of the proposed recommender system is to decrease the cold start effect. At the end of the paper, the proposed system is experimentally verified.
Annotation in english language:

References

Reference

R01:	RIV/61988987:17310/18:A1901VEM

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