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Fake Detection of Online Reviews using Semi-Supervised and Supervised Learning

Aneel Narayanapur, Pavankumar Naik, Suraksha G, Pavitra S I, Shruddha Mudigoudar, Megha Honnali
2020 International Journal of Scientific Research in Computer Science Engineering and Information Technology  
This paper introduces some semi-supervised and supervised text mining models to detect fake online reviews as well as compares the efficiency of both techniques on data set containing hotel reviews.  ...  Online reviews have great impact on today's business and commerce. Decision making for purchase of online products mostly depends on reviews given by the users.  ...  Credit card fraud We have shown several semi-supervised and supervised text mining techniques for detecting fake online reviews in this research.  ... 
doi:10.32628/cseit2063112 fatcat:ard4lmeb55hhlpc43w2x3w3myi

Detecting the spam review using tri-training

Ji Chengzhang, Dae-Ki Kang
2015 2015 17th International Conference on Advanced Communication Technology (ICACT)  
Some supervised learning methods were developed to detect spam review and some of them are considerably effective.  ...  We introduce a threeview semi-supervised method, tri-training, to exploit the large amount of unlabeled data.  ...  Semi-supervised Learning Li et al. [9] use a semi-supervised algorithm, co-training, to detect spam review, and achieve the most accurate result among semi-supervised algorithms.  ... 
doi:10.1109/icact.2015.7224822 fatcat:cogc2ulmcngibgjkpsglijhdqe

A Survey Paper on Fake Review Detection System [chapter]

Nikita V. Khairnar, Pimpri Chinchwad College of Engineering, Nigdi, Pune, India, Shruti L. Mankar, Mrunali R. Pandav, Hitesh Kotecha, Manjiri Ranjanikar
2021 New Frontiers in Communication and Intelligent Systems  
Fake reviews can be used to demote a good product or to promote a bad product, so there is a need for robust and reliable techniques to detect fake reviews which can be beneficial to the customer as well  ...  This research presents a systematic review on methods to detect spam review using different Deep Learning (DL) Approaches, Machine Learning (ML) Methods, Natural Language Processing (NLP), and Sentiment  ...  For machine learning-based proposed solutions we have discussed supervised, unsupervised, semi-supervised as well as ensemble learning-based methodologies.  ... 
doi:10.52458/978-81-95502-00-4-64 fatcat:whu5r3v5hrdknc2kbwyyv3wlyi

Detection of Fake Online Reviews using Semi-supervised and Supervised learning

Yashaswini D M
2022 International Journal for Research in Applied Science and Engineering Technology  
In order to solve this problem we uses Machine learning techniques(Supervised and semi-supervised) to detect whether the given review is fake or not with high accuracy.  ...  Along with this objective we also focus on developing models which need less data to train.Since we can't always be able to get labeled data we use semi-supervised machine learning to make use of unlabeled  ...  AREMANDLA SAI PUJITHA So in this paper the author try to develop a model using semi-supervised technique to detect fake movie reviews.  ... 
doi:10.22214/ijraset.2022.44368 fatcat:jcx4hkjcazhcnoltxjqipjfwqa

Online Fraud Review Detection Using Data Mining

2020 International journal for research in engineering application & management  
This paper introduces some semi-supervised and supervised text mining models to detect fake online reviews as well as compares the efficiency of both techniques on dataset containing hotel reviews.  ...  Opinion Spam detection is an exhausting and hard problem as there are many faux or fake reviews that have been created by organizations or by the people for various purposes.  ...  They proposed several semi-supervised learning techniques which includes Co-training, Expectation maximization, Label Propagation and Spreading and Positive Unlabelled Learning [8] .  ... 
doi:10.35291/2454-9150.2020.0416 fatcat:eo2ujzcfovdxndaqahuohc3444

A Review on Fake News Detection with Machine Learning

Prof. Swati R. Khokale
2021 International Journal for Research in Applied Science and Engineering Technology  
Machine learning has played an important role in classification of the information. This paper reviews various Machine learning approaches in detection of fake and real news.  ...  Fake news is intentionally written to mislead users to believe fake information, which makes it difficult and insignificant to detect based on news content.  ...  The Authors of the paper discuss automatic fake news inference model named as Fake Detect or It is based on textual classification and builds a deep diffusive network model to learn the representations  ... 
doi:10.22214/ijraset.2021.34379 fatcat:rc2uck6em5cd7ljcihlohggis4

GANs for Semi-Supervised Opinion Spam Detection [article]

Gray Stanton, Athirai A. Irissappane
2019 arXiv   pre-print
Apart from detecting spam reviews, spamGAN can also generate reviews with reasonable perplexity.  ...  GAN based techniques for text classification.  ...  Following are the main contributions of this paper: 1) we propose spamGAN: a semi-supervised GAN based model to detect opinion spam.  ... 
arXiv:1903.08289v2 fatcat:nwhhoslqrrdz3adkpcgsfd63fq

Application Of Machine Learning Techniques For Fake Customer Review Detection

Nupoor Shailendra Kangle, Dr. Rajeshwari Kannan, Sushma Vispute
2021 Asian journal of convergence in technology  
In our work, supervised and semi supervised learning techniques are applied to detect spam review.  ...  Hence, fake reviews or spam reviews must be detected and eliminated so as to prevent misleading potential customers.  ...  Semi-supervised Learning Semi-supervised learning is learning between unsupervised learning and supervised learning. Semisupervised used for both classification and regression.  ... 
doi:10.33130/ajct.2021v07i03.003 fatcat:vfimpfkitvhnrnnjbe4wjjivxm

Detecting Deceptive Opinion Spam using Linguistics, Behavioral and Statistical Modeling

Arjun Mukherjee
2015 Tutorials  
The second section includes detailed math and algorithms for training supervised, unsupervised, semi-supervised, and partially supervised machine learning and statistical models for deceptive opinion spam  ...  Major review hosting sites and e-commerce vendors have already made some progress in detecting fake reviews.  ... 
doi:10.3115/v1/p15-5007 dblp:conf/acl/Mukherjee15 fatcat:a5vgp4kylrekho3eeov3geqthi

A novel self-learning semi-supervised deep learning network to detect fake news on social media

Xin Li, Peixin Lu, Lianting Hu, XiaoGuang Wang, Long Lu
2021 Multimedia tools and applications  
In order to address this issue, we designed a self-learning semi-supervised deep learning network by adding a confidence network layer, which made it possible to automatically return and add correct results  ...  Despite many existing fake news datasets, comprehensive and effective algorithms for detecting fake news have become one of the major obstacles.  ...  In this paper, we designed a self-learning semi-supervised deep learning network to detect fake news on social media.  ... 
doi:10.1007/s11042-021-11065-x pmid:34093070 pmcid:PMC8170457 fatcat:ccfrshrlmzdgtehxxikhtvkrhe

Fake Reviews Detection: A Survey

Rami Mohawesh, Shuxiang Xu, Son N. Tran, Robert Ollington, Matthew Springer, Yaser Jararweh, Sumbal Maqsood
2021 IEEE Access  
It also summarises and analyses the existing techniques critically to identify gaps based on two groups: traditional statistical machine learning and deep learning methods.  ...  Consequently, the techniques for detecting fake reviews have extensively been explored in the past twelve years.  ...  [35] proposed a PU semi-supervised learning model to detect fake reviews based on review content and metadata features.  ... 
doi:10.1109/access.2021.3075573 fatcat:p33ialjjjrelfavcpicty44zxy

E-commerce Anomaly Detection: A Bayesian Semi-Supervised Tensor Decomposition Approach using Natural Gradients [article]

Anil R. Yelundur, Srinivasan H. Sengamedu, Bamdev Mishra
2018 arXiv   pre-print
Anomaly Detection has several important applications. In this paper, our focus is on detecting anomalies in seller-reviewer data using tensor decomposition.  ...  In addition, we use Polya-Gamma data augmentation for the semi-supervised Bayesian tensor decomposition.  ...  To detect more complex fake review patterns, researchers have proposed graph based approaches such as approximate bi-partite cores/lockstep behavior among reviewers [Li et al., 2016; Beutal et al., 2013  ... 
arXiv:1804.03836v3 fatcat:mz6akwan6fcexn4w4otbhq2ucq

Detection of Fake Online Reviews using ML

Mallikarjuna S B
2020 International Journal for Research in Applied Science and Engineering Technology  
This paper presents a few semi-supervised and supervised content mining models to recognize counterfeit online audits just as analyses the productivity of both procedures on dataset containing lodging  ...  CONCLUSION Several semi-supervised and supervised text mining techniques are showed for detecting fake online reviews in this research.  ...  Proposed System Proposed work, focus on some classification approaches for detecting fake online reviews, some of which are semi-supervised and others are supervised.  ... 
doi:10.22214/ijraset.2020.30950 fatcat:7aq4mkyq2nhyvmp54qgah6xpui

Machine learning Techniques for Hotel Online Reputation

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
Supervised machine learning technique, Text mining, Unsupervised machine learning technique, Semi-supervised learning, Reinforcement learning etc we may detect the fake reviews.  ...  This paper gives some notions of using machine learning techniques in analysis of past online reviews of hotels, Based on the observation it also suggest the optimal machine learning technique for a particular  ...  SEMI-SUPERVISED LEARNING Semi-supervised learning algorithm includes both labelled and unlabeled data.  ... 
doi:10.35940/ijitee.i8004.078919 fatcat:cjjvyqbwj5fs5e4trzubylucni

Cloud based Framework for Fake Review Detection

Md. Towhidul Islam Robin
2019 Global Journal of Computer Science and Technology  
Using Natural Language Processing, many methods have already been developed to detect fake reviews, especially reviews written in the English language.  ...  Firstly, the system checks whether the review is fake or not. Secondly, it also checks the authenticity of the reviewer.  ...  Literature Review For identifying fake reviews Supervised, Unsupervised, and Semi-supervised methods have been used so far where most of the models based on supervised learning.  ... 
doi:10.34257/gjcstdvol19is4pg9 fatcat:jqlwreklkrhahjn5iilv76t6qq
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