Spam review detection using LSTM autoencoder: an unsupervised approach
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DOI: 10.1007/s10660-020-09413-4
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References listed on IDEAS
- Ajay Rastogi & Monica Mehrotra, 2017. "Opinion Spam Detection in Online Reviews," Journal of Information & Knowledge Management (JIKM), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 1-38, December.
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Cited by:
- Ben Jabeur, Sami & Ballouk, Hossein & Ben Arfi, Wissal & Sahut, Jean-Michel, 2023. "Artificial intelligence applications in fake review detection: Bibliometric analysis and future avenues for research," Journal of Business Research, Elsevier, vol. 158(C).
- Fadhila Lachekhab & Messouada Benzaoui & Sid Ahmed Tadjer & Abdelkrim Bensmaine & Hichem Hamma, 2024. "LSTM-Autoencoder Deep Learning Model for Anomaly Detection in Electric Motor," Energies, MDPI, vol. 17(10), pages 1-18, May.
- Shugang Li & Fang Liu & Yuqi Zhang & Boyi Zhu & He Zhu & Zhaoxu Yu, 2022. "Text Mining of User-Generated Content (UGC) for Business Applications in E-Commerce: A Systematic Review," Mathematics, MDPI, vol. 10(19), pages 1-26, September.
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Keywords
E-commerce; Autoencoder neural network; Machine learning; Spam detection; Unsupervised learning; Long short-term memory;All these keywords.
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