Trust-based Collective View Prediction

Trust-based Collective View Prediction

Trust-based Collective View Prediction

Trust-based Collective View Prediction by Tiejian Luo, Su Chen, Guandong Xu and Jia Zhou

Collective view prediction is to judge the opinions of an active web user based on unknown elements by referring to the collective mind of the whole community. Content-based recommendation and collaborative filtering are two mainstream collective view prediction techniques. They generate predictions by analyzing the text features of the target object or the similarity of users’ past behaviors. Still, these techniques are vulnerable to the artificially-injected noise data, because they are not able to judge the reliability and credibility of the information sources. Trust-based Collective View Prediction describes new approaches for tackling this problem by utilizing users’ trust relationships from the perspectives of fundamental theory, trust-based collective view prediction algorithms and real case studies.

Ebook format: PDF
Ebook page: 150
File size: 3.90 MB

$40.00