Implementation of a Product-Recommender System in an IoT-Based Smart Shopping Using Fuzzy Logic and Apriori Algorithm

dc.authoridHeidari, Arash/0000-0003-4279-8551
dc.authoridJafari Navimipour, Nima/0000-0002-5514-5536
dc.authorwosidHeidari, Arash/AAK-9761-2021
dc.authorwosidJafari Navimipour, Nima/AAF-5662-2021
dc.contributor.authorYan, Shu-Rong
dc.contributor.authorPirooznia, Sina
dc.contributor.authorHeidari, Arash
dc.contributor.authorNavimipour, Nima Jafari
dc.contributor.authorUnal, Mehmet
dc.date.accessioned2023-10-19T15:11:55Z
dc.date.available2023-10-19T15:11:55Z
dc.date.issued2022
dc.department-temp[Yan, Shu-Rong] Hunan Univ, Sch Business Adm, Changsha 410082, Peoples R China; [Pirooznia, Sina; Heidari, Arash] Islamic Azad Univ, Tabriz Branch, Dept Comp Engn, Tabriz, Iran; [Navimipour, Nima Jafari] Kadir Has Univ, Fac Engn & Nat Sci, Dept Comp Engn, Istanbul, Turkey; [Unal, Mehmet] Nisantasi Univ, Dept Comp Engn, Istanbul, Turkeyen_US
dc.description.abstractThe Internet of Things (IoT) has recently become important in accelerating various functions, from manufacturing and business to healthcare and retail. A recommender system can handle the problem of information and data buildup in IoT-based smart commerce systems. These technologies are designed to determine users' preferences and filter out irrelevant information. Identifying items and services that customers might be interested in and then convincing them to buy is one of the essential parts of effective IoT-based smart shopping systems. Due to the relevance of product-recommender systems from both the consumer and shop perspectives, this article presents a new IoT-based smart product-recommender system based on an apriori algorithm and fuzzy logic. The suggested technique employs association rules to display the interdependencies and linkages among many data objects. The most common use of association rule discovery is shopping cart analysis. Customers' buying habits and behavior are studied based on the numerous goods they place in their shopping carts. As a result, the association rules are generated using a fuzzy system. The apriori algorithm then selects the product based on the provided fuzzy association rules. The results revealed that the suggested technique had achieved acceptable results in terms of mean absolute error, root-mean-square error, precision, recall, diversity, novelty, and catalog coverage when compared to cutting-edge methods. Finally, themethod helps increase recommender systems' diversity in IoT-based smart shopping.en_US
dc.description.sponsorshipkey program of the National Social Science Foundation of China [18AJY013]en_US
dc.description.sponsorshipThis work was supported by the key program of the National Social Science Foundation of China under Grant 18AJY013. Reviewof this manuscript was arranged by Department Editor D. Cetindamar.en_US
dc.identifier.citation13
dc.identifier.doi10.1109/TEM.2022.3207326en_US
dc.identifier.issn0018-9391
dc.identifier.issn1558-0040
dc.identifier.scopus2-s2.0-85141470160en_US
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1109/TEM.2022.3207326
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5279
dc.identifier.wosWOS:001007844500001en_US
dc.identifier.wosqualityQ1
dc.khas20231019-WoSen_US
dc.language.isoenen_US
dc.publisherIEEE-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Transactions on Engineering Managementen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectApriori algorithmen_US
dc.subjectfilteringen_US
dc.subjectfuzzy logicen_US
dc.subjectInternet of thingsen_US
dc.subjectrecommender systemsen_US
dc.subjectshopping carten_US
dc.subjectsmarteningen_US
dc.titleImplementation of a Product-Recommender System in an IoT-Based Smart Shopping Using Fuzzy Logic and Apriori Algorithmen_US
dc.typeArticleen_US
dspace.entity.typePublication

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