Fake review detection on online E-commerce platforms: a systematic literature review
H Paul, A Nikolaev - Data Mining and Knowledge Discovery, 2021 - Springer
The increasing popularity of online review systems motivates malevolent intent in competing
sellers and service providers to manipulate consumers by fabricating product/service …
sellers and service providers to manipulate consumers by fabricating product/service …
Shilling attacks against collaborative recommender systems: a review
M Si, Q Li - Artificial Intelligence Review, 2020 - Springer
Collaborative filtering recommender systems (CFRSs) have already been proved effective to
cope with the information overload problem since they merged in the past two decades …
cope with the information overload problem since they merged in the past two decades …
A framework for big data analytics in commercial social networks: A case study on sentiment analysis and fake review detection for marketing decision-making
User-generated content about brands is an important source of big data that can be
transformed into valuable information. A huge number of items are reviewed and rated by …
transformed into valuable information. A huge number of items are reviewed and rated by …
Gcn-based user representation learning for unifying robust recommendation and fraudster detection
In recent years, recommender system has become an indispensable function in all e-
commerce platforms. The review rating data for a recommender system typically comes from …
commerce platforms. The review rating data for a recommender system typically comes from …
CARM: Confidence-aware recommender model via review representation learning and historical rating behavior in the online platforms
The recommendation systems in the online platforms often suffer from the rating data
sparseness and information overload issues. Previous studies on this topic often leverage …
sparseness and information overload issues. Previous studies on this topic often leverage …
A Survey on the Applications of Semi-supervised Learning to Cyber-security
Machine Learning's widespread application owes to its ability to develop accurate and
scalable models. In cyber-security, where labeled data is scarce, Semi-Supervised Learning …
scalable models. In cyber-security, where labeled data is scarce, Semi-Supervised Learning …
Opinion fraud detection via neural autoencoder decision forest
Online reviews play an important role in influencing buyers' daily purchase decisions.
However, fake and meaningless reviews, which cannot reflect users' genuine purchase …
However, fake and meaningless reviews, which cannot reflect users' genuine purchase …
Deceptive opinion spam detection approaches: a literature survey
Nowadays, a large number of customers purchase products and services online. Customers
can write their opinions in reviews to express the value and quality of purchased goods and …
can write their opinions in reviews to express the value and quality of purchased goods and …
Detecting spammer groups from product reviews: a partially supervised learning model
Nowadays, online product reviews play a crucial role in the purchase decision of
consumers. A high proportion of positive reviews will bring substantial sales growth, while …
consumers. A high proportion of positive reviews will bring substantial sales growth, while …
Robust model-based reliability approach to tackle shilling attacks in collaborative filtering recommender systems
As the use of recommender systems becomes generalized in society, the interest in varying
the orientation of their recommendations is increasing. There are shilling attacks' strategies …
the orientation of their recommendations is increasing. There are shilling attacks' strategies …