Predictivity of Category Based Human Navigation and the Effect of Navigation Path Length on the Prediction Accuracy in Knowledge Networks

dc.contributor.authorCifci, Evren
dc.contributor.authorGöktürk, Mehmet
dc.date.accessioned2025-10-29T12:08:10Z
dc.date.issued2022
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description3rd International Conference on Communications, Information, Electronic and Energy Systems, CIEES 2022 -- Virtual, Online; Meridian Bolyarski Hotel -- 185703
dc.description.abstractIn web sites containing large amount of information, systems which help visitors access the contents they are interested in, significantly increase the usability of the sites. Knowing the category of the content that the user wants to access is important to offer more qualified suggestions and advertisements to the user. On the other hand, as the user continues to navigate in the site, more navigation data is obtained from him, which may potentially be used for better predictions.In this study, the predictability of users' category-based navigation and the effect of the length of the navigation path on the prediction accuracy in knowledge networks is investigated using LSTM classifiers. © 2023 Elsevier B.V., All rights reserved.
dc.description.sponsorshipVIPIMEX Ltd, Premium Partner of Konica Minolta Bulgaria
dc.identifier.doi10.1109/CIEES55704.2022.9990641
dc.identifier.isbn9781665491495
dc.identifier.scopus2-s2.0-85146488232
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://doi.org/10.1109/CIEES55704.2022.9990641
dc.identifier.urihttps://hdl.handle.net/20.500.14854/14343
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20251020
dc.subjecthci
dc.subjecthuman computer interaction
dc.subjectLSTM
dc.subjectnavigation prediction
dc.subjectweb navigation
dc.titlePredictivity of Category Based Human Navigation and the Effect of Navigation Path Length on the Prediction Accuracy in Knowledge Networks
dc.typeConference Object

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