Cargando…

Fake review identification and utility evaluation model using machine learning

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 growth in the quality of online reviews seems to be s...

Descripción completa

Detalles Bibliográficos
Autores principales:	Choi, Wonil, Nam, Kyungmin, Park, Minwoo, Yang, Seoyi, Hwang, Sangyoon, Oh, Hayoung
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2023
Materias:	Artificial Intelligence
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9893788/ https://www.ncbi.nlm.nih.gov/pubmed/36744111 http://dx.doi.org/10.3389/frai.2022.1064371

Ejemplares similares

Graph Learning for Fake Review Detection
por: Yu, Shuo, et al.
Publicado: (2022)

Identification of Scams in Initial Coin Offerings With Machine Learning
por: Karimov, Bedil, et al.
Publicado: (2021)

Deep fake detection using cascaded deep sparse auto-encoder for effective feature selection
por: Balasubramanian, Saravana Balaji, et al.
Publicado: (2022)

Location and Language Independent Fake Rumor Detection Through Epidemiological and Structural Graph Analysis of Social Connections
por: Serpanos, Dimitrios, et al.
Publicado: (2022)

Satellite imagery and machine learning for identification of aridity risk in central Java Indonesia
por: Prasetyo, Sri Yulianto Joko, et al.
Publicado: (2021)

Machine learning and deep learning approaches in IoT
por: Javed, Abqa, et al.
Publicado: (2023)

Designing and Evaluating the Usability of a Machine Learning API for Rapid Prototyping Music Technology
por: Bernardo, Francisco, et al.
Publicado: (2020)

Editorial: Machine Learning for Water Resources
por: Mariethoz, Gregoire, et al.
Publicado: (2021)

Opportunities for human factors in machine learning
por: Baweja, Jessica A., et al.
Publicado: (2023)

GDP Forecasting: Machine Learning, Linear or Autoregression?
por: Maccarrone, Giovanni, et al.
Publicado: (2021)

A Survey of Topological Machine Learning Methods
por: Hensel, Felix, et al.
Publicado: (2021)

Integration of AI and Machine Learning in Radiotherapy QA
por: Chan, Maria F., et al.
Publicado: (2020)

Leveraging explanations in interactive machine learning: An overview
por: Teso, Stefano, et al.
Publicado: (2023)

Using machine learning for healthcare treatment planning
por: Dubey, Snigdha, et al.
Publicado: (2023)

Predicting ward transfer mortality with machine learning
por: Lezama, Jose L., et al.
Publicado: (2023)

Corrigendum: Opportunities for human factors in machine learning
por: Baweja, Jessica A., et al.
Publicado: (2023)

A systematic review on machine learning models for online learning and examination systems
por: Kaddoura, Sanaa, et al.
Publicado: (2022)

Impact of Box-Cox Transformation on Machine-Learning Algorithms
por: Blum, Luca, et al.
Publicado: (2022)

Applied Machine Learning for Stochastic Local Volatility Calibration
por: Hakala, Jürgen
Publicado: (2019)

Topology Applied to Machine Learning: From Global to Local
por: Adams, Henry, et al.
Publicado: (2021)

Roof type classification with innovative machine learning approaches
por: Ölçer, Naim, et al.
Publicado: (2023)

Supervised machine learning models for depression sentiment analysis
por: Obagbuwa, Ibidun Christiana, et al.
Publicado: (2023)

Evaluation of Multiple Machine Learning Models for Predicting Number of Anti-VEGF Injections in the Comparison of AMD Treatment Trials (CATT)
por: Chandra, Rajat S., et al.
Publicado: (2023)

Integrated Evolutionary Learning: An Artificial Intelligence Approach to Joint Learning of Features and Hyperparameters for Optimized, Explainable Machine Learning
por: de Lacy, Nina, et al.
Publicado: (2022)

Predictions of bitcoin prices through machine learning based frameworks
por: Cocco, Luisanna, et al.
Publicado: (2021)

Generalizable Machine Learning in Neuroscience Using Graph Neural Networks
por: Wang, Paul Y., et al.
Publicado: (2021)

Algorithmic Probability-Guided Machine Learning on Non-Differentiable Spaces
por: Hernández-Orozco, Santiago, et al.
Publicado: (2021)

Survey on graph embeddings and their applications to machine learning problems on graphs
por: Makarov, Ilya, et al.
Publicado: (2021)

Predicting Cervical Cancer Outcomes: Statistics, Images, and Machine Learning
por: Luo, Wei
Publicado: (2021)

A United States Fair Lending Perspective on Machine Learning
por: Hall, Patrick, et al.
Publicado: (2021)

A Comparative Study of Machine Learning Methods for Persistence Diagrams
por: Barnes, Danielle, et al.
Publicado: (2021)

Understanding Musical Predictions With an Embodied Interface for Musical Machine Learning
por: Martin, Charles Patrick, et al.
Publicado: (2020)

Fusion of text and graph information for machine learning problems on networks
por: Makarov, Ilya, et al.
Publicado: (2021)

Machine Learning Applied to the Search for Nonlinear Features in Breeding Populations
por: Gabur, Iulian, et al.
Publicado: (2022)

Predictive keywords: Using machine learning to explain document characteristics
por: Kyröläinen, Aki-Juhani, et al.
Publicado: (2023)

Accurately predicting hit songs using neurophysiology and machine learning
por: Merritt, Sean H., et al.
Publicado: (2023)

Machine learning algorithms in microbial classification: a comparative analysis
por: Wu, Yuandi, et al.
Publicado: (2023)

Classification model for accuracy and intrusion detection using machine learning approach
por: Agarwal, Arushi, et al.
Publicado: (2021)

Machine Learning Detects Anti-DENV Signatures in Antibody Repertoire Sequences
por: Horst, Alexander, et al.
Publicado: (2021)

A Machine Learning Approach to Personalize Computerized Cognitive Training Interventions
por: Vladisauskas, Melina, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_koncd69n0mg1lg5kcgdt9b5o5a