Please use this identifier to cite or link to this item: http://repository.kln.ac.lk/handle/123456789/27341
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dc.contributor.authorGunawardhana, Kalinga-
dc.contributor.authorKumara, B.T.G.S.-
dc.contributor.authorRathnayake, R.M.K.T.-
dc.contributor.authorJayaweera, Prasad M.-
dc.date.accessioned2024-01-16T04:26:53Z-
dc.date.available2024-01-16T04:26:53Z-
dc.date.issued2023-
dc.identifier.citationGunawardhana Kalinga; Kumara B.T.G.S.; Rathnayake R.M.K.T.; Jayaweera Prasad M. (2023). Effectiveness of Machine Learning Algorithms on Battling Counterfeit Items in E-commerce Marketplaces, International Research Conference on Smart Computing and Systems Engineering (SCSE 2023), Department of Industrial Management, Faculty of Science, University of Kelaniya Sri Lanka. Page 3en_US
dc.identifier.urihttp://repository.kln.ac.lk/handle/123456789/27341-
dc.description.abstractFor e-commerce marketplaces, counterfeit goods are a major issue since they endanger public safety in addition to causing customer unhappiness and revenue loss. Traditional techniques to identify fake goods in online marketplaces take too long and have a narrow reach, hence they are ineffective. Machine learning algorithms have become a potential tool for swiftly and precisely identifying counterfeit goods in recent years. The usefulness of two machine learning algorithms in identifying fake goods in online marketplaces is examined in this research. The study assesses the performance using a sizable dataset of descriptions, title, prices and seller names from many well-known e-commerce platforms. The study's findings show that machine learning algorithms significantly affect the detection of fake goods in online marketplaces.en_US
dc.publisherDepartment of Industrial Management, Faculty of Science, University of Kelaniya Sri Lankaen_US
dc.subjectcounterfeit listing, decision trees, e-commerce, machine learning, random foresten_US
dc.titleEffectiveness of Machine Learning Algorithms on Battling Counterfeit Items in E-commerce Marketplacesen_US
Appears in Collections:Smart Computing and Systems Engineering - 2023 (SCSE 2023)

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