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Toward Point-of-Interest Recommendation Systems: A Critical Review on Deep-Learning Approaches

Safavi, Sadaf; Jalali, Mehrdad ORCID iD icon 1; Houshmand, Mahboobeh
1 Institut für Funktionelle Grenzflächen (IFG), Karlsruher Institut für Technologie (KIT)

Abstract:

In recent years, location-based social networks (LBSNs) that allow members to share their location and provide related services, and point-of-interest (POIs) recommendations which suggest attractive places to visit, have become noteworthy and useful for users, research areas, industries, and advertising companies. The POI recommendation system combines different information sources and creates numerous research challenges and questions. New research in this field utilizes deep-learning techniques as a solution to the issues because it has the ability to represent the nonlinear relationship between users and items more effectively than other methods. Despite all the obvious improvements that have been made recently, this field still does not have an updated and integrated view of the types of methods, their limitations, features, and future prospects. This paper provides a systematic review focusing on recent research on this topic. First, this approach prepares an overall view of the types of recommendation methods, their challenges, and the various influencing factors that can improve model performance in POI recommendations, then it reviews the traditional machine-learning methods and deep-learning techniques employed in the POI recommendation and analyzes their strengths and weaknesses. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000149743
Veröffentlicht am 10.08.2022
Originalveröffentlichung
DOI: 10.3390/electronics11131998
Scopus
Zitationen: 6
Web of Science
Zitationen: 6
Dimensions
Zitationen: 8
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Funktionelle Grenzflächen (IFG)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2079-9292
KITopen-ID: 1000149743
HGF-Programm 43.33.11 (POF IV, LK 01) Adaptive and Bioinstructive Materials Systems
Erschienen in Electronics
Verlag MDPI
Band 11
Heft 13
Seiten Art.Nr. 1998
Bemerkung zur Veröffentlichung Gefördert durch den KIT-Publikationsfonds
Vorab online veröffentlicht am 26.06.2022
Nachgewiesen in Web of Science
Dimensions
Scopus
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