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Analysing the effect of platform and operating system features on predicting consumers' purchase intent using machine learning algorithms

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Predicting future consumer browsing and purchase behaviour has become crucial to many marketing platforms. Consumer purchase intention is one of the main inputs used as a measurement for consumer demand for new products. In addition, identifying consumers' purchase intent play an important role in recommender systems. In this paper, the effect of using different platforms on users' behaviours is explored. In addition, the effect of users' platforms and their purchase intentions behaviours are investigated. We conduct computational experiments using different machine learning algorithms in order to investigate the using users' operating system and platform types as features. The results showed that the users' purchase intention and behaviours are correlated with these features.
Original languageEnglish
Title of host publicationProceedings of the 12th International Joint Conference on Knowledge Discovery
Subtitle of host publicationKDIR
EditorsAna Fred, Joaquim Filipe
PublisherSciTePress
Number of pages8
Volume1
ISBN (Print)978-989-758-474-9
DOIs
Publication statusPublished - 12 Nov 2020
Event12th International Joint Conference on Knowledge Discovery -
Duration: 2 Nov 20204 Nov 2020
http://www.kdir.ic3k.org/

Conference

Conference12th International Joint Conference on Knowledge Discovery
Abbreviated titleKDIR
Period2/11/204/11/20
Internet address

Documents

  • KDIR

    Accepted author manuscript (Post-print), 174 KB, PDF document

Related information

Relations Get citation (various referencing formats)

ID: 22662176