Zobrazeno 1 - 10
of 157
pro vyhledávání: '"fake review detection"'
Autor:
Syed Abdullah Ashraf, Aariz Faizan Javed, Sreevatsa Bellary, Pradip Kumar Bala, Prabin Kumar Panigrahi
Publikováno v:
Journal of Theoretical and Applied Electronic Commerce Research, Vol 19, Iss 2, Pp 1517-1558 (2024)
Driven by motives of profit and competition, fake reviews are increasingly used to manipulate product ratings. This trend has caught the attention of academic researchers and international regulatory bodies. Current methods for spotting fake reviews
Externí odkaz:
https://doaj.org/article/f0d8cdb3c4be4cb8a8bd9fa2470cce2d
Autor:
Samia M. Abd-Alhalem, Hesham Arafat Ali, Naglaa F. Soliman, Abeer D. Algarni, Hanaa Salem Marie
Publikováno v:
IEEE Access, Vol 12, Pp 116055-116070 (2024)
In the contemporary digital marketplace, the proliferation of online consumer reviews has a pivotal influence on purchasing decisions. Concurrently, the prevalence of spurious reviews poses a substantial risk to the integrity of e-commerce, misleadin
Externí odkaz:
https://doaj.org/article/9b78913ea9014a69a7aafdc20d4d6d0f
Publikováno v:
e-Prime: Advances in Electrical Engineering, Electronics and Energy, Vol 8, Iss , Pp 100506- (2024)
Sentiment analysis plays a vital role in real time environment for knowing the history of a product or any other specific entity. Due to large number of users in the www, chances are there that many fake users may upload the fake reviews to damage th
Externí odkaz:
https://doaj.org/article/481050be4c1144f5b863b5397c3390ac
Publikováno v:
Journal of Theoretical and Applied Electronic Commerce Research, Vol 18, Iss 4, Pp 2188-2216 (2023)
The rapid growth of e-commerce has significantly increased the demand for advanced techniques to address specific tasks in the e-commerce field. In this paper, we present a brief survey of machine learning and deep learning techniques in the context
Externí odkaz:
https://doaj.org/article/ee21c16ec91848e0afb447f561c1d8fc
Publikováno v:
Jisuanji kexue yu tansuo, Vol 17, Iss 2, Pp 428-441 (2023)
As a hot spot in machine learning, graph neural networks (GNN) have recently begun to be applied in the field of fraud detection involving user reviews. In reality, the collected user comments involve diverse fields and complex information, and the f
Externí odkaz:
https://doaj.org/article/0c1eb9d96d17403cb562f9eb1e77076f
Akademický článek
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Akademický článek
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Publikováno v:
Computers in Human Behavior Reports, Vol 10, Iss , Pp 100278- (2023)
Background: Consumers rely heavily on online user reviews when shopping online and cybercriminals produce fake reviews to manipulate consumer opinion. Much prior research focuses on the automated detection of these fake reviews, which are far from pe
Externí odkaz:
https://doaj.org/article/0569323b59864d53990b712d78b9b691
Publikováno v:
IEEE Access, Vol 10, Pp 128622-128655 (2022)
Online reviews influence consumers’ purchasing decisions. However, identifying fake online reviews automatically remains a complex problem, and current detection approaches are inefficient in preventing the spread of fake reviews. The literature on
Externí odkaz:
https://doaj.org/article/aaf735b37acf41e3a467b3716796a232
Publikováno v:
Frontiers in Artificial Intelligence, Vol 5 (2023)
Due to the structural growth of e-commerce platforms, the frequency of exchange of opinions and the number of online reviews of platform participants related to products are increasing. However, given the growth of fake reviews, the corresponding gro
Externí odkaz:
https://doaj.org/article/3a506ec5ec3a4f5196f94be1f8d5736e