Trustworthiness, diversity and inference in recommendation systems

Trustworthiness, diversity and inference in recommendation systems

Recommendation systems are information filtering systems that help users effectively and efficiently explore large amount of information and identify items of interest. Accurate predictions of users' interests improve user satisfaction and are beneficial to business or service providers. Resear...

Full description

Bibliographic Details
Main Author: Chen, Cheng
Other Authors: Wu, Kui
Language:English
en
Published: 2016
Subjects:
Bipartite Graphs
Matchings
NP-hardness
Linear Programming
Submodular Systems
Recommendation Systems
Anomaly Detection
Community Question and Answer Websites
Paid Posters
Adaptive Detection Systems
Weighted Bipartite b-Matching
Conflict Constraints
Optimization
Approximation
Reverse Engineering of Recommendations
Wi-Fi Data Mining
Profile Inference
Copula Modelling
Online Access:http://hdl.handle.net/1828/7576

Internet

http://hdl.handle.net/1828/7576

Similar Items