Differential privacy in collaborative filtering recommender systems: a review
State-of-the-art recommender systems produce high-quality recommendations to support
users in finding relevant content. However, through the utilization of users' data for …
users in finding relevant content. However, through the utilization of users' data for …
Objectives and state-of-the-art of location-based social network recommender systems
Z Ding, X Li, C Jiang, M Zhou - Acm Computing Surveys (Csur), 2018 - dl.acm.org
Because of the widespread adoption of GPS-enabled devices, such as smartphones and
GPS navigation devices, more and more location information is being collected and …
GPS navigation devices, more and more location information is being collected and …
Towards comprehensive support for privacy preservation cross-organization business process mining
More and more business requirements are crossing organizational boundaries. There
comes the cross-organization business process management, and its modeling is a …
comes the cross-organization business process management, and its modeling is a …
A game theoretic approach for privacy preserving model in IoT-based transportation
Internet of Things applications using sensors and actuators raise new privacy related
threats, such as drivers and vehicles tracking and profiling. These threats can be addressed …
threats, such as drivers and vehicles tracking and profiling. These threats can be addressed …
A deep Boltzmann machine and multi-grained scanning forest ensemble collaborative method and its application to industrial fault diagnosis
The essence of big data-based intelligent industrial fault diagnosis lies in the process of
machine learning and feature engineering. Deep learning methods can discover the …
machine learning and feature engineering. Deep learning methods can discover the …
DPLCF: differentially private local collaborative filtering
Most existing recommender systems leverage users' complete original behavioral logs,
which are collected from mobile devices and stored by the service provider and further fed …
which are collected from mobile devices and stored by the service provider and further fed …
[HTML][HTML] A privacy-preserving mobile application recommender system based on trust evaluation
K Xu, W Zhang, Z Yan - Journal of computational science, 2018 - Elsevier
Too many mobile applications in App stores results in information overload in App market.
Mobile users are confused in choosing suitable and trustworthy mobile applications due to a …
Mobile users are confused in choosing suitable and trustworthy mobile applications due to a …
Robust transfer learning for cross-domain collaborative filtering using multiple rating patterns approximation
M He, J Zhang, P Yang, K Yao - … conference on web search and data …, 2018 - dl.acm.org
Collaborative filtering techniques are a common approach for building recommendations,
and have been widely applied in real recommender systems. However, collaborative …
and have been widely applied in real recommender systems. However, collaborative …
Locally differentially private item-based collaborative filtering
T Guo, J Luo, K Dong, M Yang - Information Sciences, 2019 - Elsevier
Recently, item-based collaborative filtering has attracted a lot of attention. It recommends to
users new items which may be of interests to them, based on their reported historical data …
users new items which may be of interests to them, based on their reported historical data …
Road surface temperature prediction based on gradient extreme learning machine boosting
The expressway is extremely important to transportation, but high road-surface temperatures
(RST) can cause many traffic accidents. Most of the hourly RST prediction models are based …
(RST) can cause many traffic accidents. Most of the hourly RST prediction models are based …