Analysing Content Ratings of Google Apps with Ensemble Learning

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dc.authorscopusid56557054300
dc.authorscopusid57205616621
dc.authorscopusid36503422100
dc.contributor.authorAtagün, Ercan
dc.contributor.authorTimuçin, Tunahan
dc.contributor.authorBiroğul, S.
dc.date.accessioned2023-07-26T11:55:02Z
dc.date.available2023-07-26T11:55:02Z
dc.date.issued2022
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description.abstractGoogle Play was launched under the name of Android Market and made its reputation known all over the world. The mobile application market, which is a package manager developed by Google for Android users, contains applications that appeal to many areas and age ranges. Applications are spread over a wide range of uses. Thus, the amount and size of the data increased, and this situation began to attract the attention of researchers. The excessive increase in the number of applications makes it difficult for parents to follow up on the content. To provide the content rating of applications on Google Play, it is needed to be classified by machine learning methods. In this study, content rating classification was made by analyzing “Category, Rating, Reviews, Size, Installs, Type, Genres, Last Updated, Current Version, Android Version” features of 10757 applications on Google Play, Ensemble Learning methods (Adaboost, Bagging, Random Forest, Stacking), Logistic Regression, Artificial Neural Network, K-Nearest Neighbors algorithms. © 2022, TUBITAK. All rights reserved.en_US
dc.identifier.doi10.31202/ecjse.1059822
dc.identifier.endpage1050en_US
dc.identifier.issn2148-3736
dc.identifier.issue3en_US
dc.identifier.scopus2-s2.0-85139793376en_US
dc.identifier.scopusqualityQ4en_US
dc.identifier.startpage1038en_US
dc.identifier.urihttps://doi.org/10.31202/ecjse.1059822
dc.identifier.urihttps://hdl.handle.net/20.500.12684/12982
dc.identifier.volume9en_US
dc.indekslendigikaynakScopusen_US
dc.institutionauthorAtagün, Ercan
dc.institutionauthorTimuçin, Tunahan
dc.institutionauthorBiroğul, S.
dc.language.isoenen_US
dc.publisherTUBITAKen_US
dc.relation.ispartofEl-Cezeri Journal of Science and Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmz$2023V1Guncelleme$en_US
dc.subjectclassificationen_US
dc.subjectcontent ratingen_US
dc.subjectEnsemble learningen_US
dc.subjectgoogle appsen_US
dc.titleAnalysing Content Ratings of Google Apps with Ensemble Learningen_US
dc.title.alternativeTopluluk Öğrenmesi ile Google Uygulamalarının İçerik Derecelendirmelerini Analiz Etmeen_US
dc.typeArticleen_US

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