Publication:
Complaint detection and classification of customer reviews

dc.contributor.coauthorBayrak, Ahmet Tuğrul
dc.contributor.coauthorYıldız, Eray
dc.contributor.coauthorÖzbek, Eyüp Erkan
dc.contributor.kuauthorTürker, Bekir Berker
dc.contributor.kuprofilePhD Student
dc.contributor.schoolcollegeinstituteGraduate School of Sciences and Engineering
dc.contributor.yokidN/A
dc.date.accessioned2024-11-09T23:50:16Z
dc.date.issued2021
dc.description.abstractIn a world where competition and technology usage increase consistently, customer satisfaction has become important for companies. In this study, the customer reviews, obtained from the results of the surveys that are made via different channels, are analyzed and when a problem is detected, a quick solution is aimed. For the complaint detection and classification on the customer reviews process, long short-term memory, which is a recurrent neural network, is applied. A data set from the tourism industry is labelled to carry out the proposed method. The results retrieved on performing the method on the data, which is relatively larger than the similar works in literature, are acceptable and the proposed model works in real-time.
dc.description.indexedbyWoS
dc.description.indexedbyScopus
dc.description.openaccessNO
dc.description.publisherscopeInternational
dc.identifier.doi10.1109/SIU53274.2021.9478016
dc.identifier.isbn978-1-6654-3649-6
dc.identifier.quartileN/A
dc.identifier.scopus2-s2.0-85111443288
dc.identifier.urihttp://dx.doi.org/10.1109/SIU53274.2021.9478016
dc.identifier.urihttps://hdl.handle.net/20.500.14288/14516
dc.identifier.wos808100700257
dc.keywordsMulti label text classification
dc.keywordsRecurrent neural network
dc.keywordsLong short term memory
dc.keywordsComplaint detection
dc.languageTurkish
dc.publisherIEEE
dc.source29th IEEE Conference on Signal Processing and Communications Applications (Siu 2021)
dc.subjectCivil engineering
dc.subjectElectrical electronics engineering
dc.subjectTelecommunication
dc.titleComplaint detection and classification of customer reviews
dc.typeConference proceeding
dspace.entity.typePublication
local.contributor.authoridN/A
local.contributor.kuauthorTürker, Bekir Berker

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