With the rapid development of e-business, personalized recommendation has become core competence for enterprises to gain profits and improve customer satisfaction. Although collaborative filtering is the most successful approach for building a recommender system, it suffers from “shilling” attacks. In recent years, the research on shilling attacks has been greatly improved. However, the approaches suffer from serious problem in attack model dependency and high computational cost. To solve the problem, an approach for the detection of abnormal item is proposed in this paper. In the paper, two common features of all attack models are analyzed at first. A revised bottom-up discretized approach is then proposed based on time intervals and the f...
E-commerce recommender systems are vulnerable to different types of shilling attack where the attack...
Recommender systems have emerged in the past several years as an effective way to help people cope w...
Recommender systems play an essential role in our digital society as they suggest products to purcha...
Copyright © 2014 Min Gao et al.This is an open access article distributed under the Creative Commons...
In recent years, recommender systems have become an effective method to process information overload...
Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as ...
Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attac...
Collaborative filtering has been widely used in recommendation systems to recommend items that users...
Recommender systems are widely used, in social networks and online stores, to overcome the problems ...
The problem of identifying shilling attacks, which are aimed at forming false ratings of objects in ...
The problem of shilling attacks detecting in e-commerce systems is considered. The purpose of such a...
The problem of shilling attacks detecting in e-commerce systems is considered. The purpose of such a...
Collaborative filtering techniques have been successfully em-ployed in recommender systems in order ...
Collaborative filtering recommenders are highly vulner-able to malicious attacks designed to affect ...
The stability and reliability of filtration and recommender systems are crucial for continuous opera...
E-commerce recommender systems are vulnerable to different types of shilling attack where the attack...
Recommender systems have emerged in the past several years as an effective way to help people cope w...
Recommender systems play an essential role in our digital society as they suggest products to purcha...
Copyright © 2014 Min Gao et al.This is an open access article distributed under the Creative Commons...
In recent years, recommender systems have become an effective method to process information overload...
Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as ...
Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attac...
Collaborative filtering has been widely used in recommendation systems to recommend items that users...
Recommender systems are widely used, in social networks and online stores, to overcome the problems ...
The problem of identifying shilling attacks, which are aimed at forming false ratings of objects in ...
The problem of shilling attacks detecting in e-commerce systems is considered. The purpose of such a...
The problem of shilling attacks detecting in e-commerce systems is considered. The purpose of such a...
Collaborative filtering techniques have been successfully em-ployed in recommender systems in order ...
Collaborative filtering recommenders are highly vulner-able to malicious attacks designed to affect ...
The stability and reliability of filtration and recommender systems are crucial for continuous opera...
E-commerce recommender systems are vulnerable to different types of shilling attack where the attack...
Recommender systems have emerged in the past several years as an effective way to help people cope w...
Recommender systems play an essential role in our digital society as they suggest products to purcha...