Paper Info
Title
FluidRating: A time-evolving rating scheme in trust-based recommendation systems using fluid dynamics
Abstract
The goal of a trust-based recommendation system is to predict unknown ratings based on the ratings expressed by trusted friends. However, most of the existing work only considers the ratings at the current time slot. In real life, a user receives the influence of different opinions sequentially; accordingly, his opinion evolves over time. We propose a novel rating prediction scheme, FluidRating, which uses fluid dynamics theory to reveal the time-evolving formulation process of human opinions. The recommendation is modeled as fluid with two dimensions: the temperature is taken as the “opinion/rating,” and its volume is deemed as the “persistency,” representing how much one insists on his opinion. When new opinions come, each user refines his opinion through a round of fluid exchange with his neighbors. Opinions from multiple rounds are aggregated to gain a final prediction; both uniform and non-uniform aggregation are tested. Moreover, Three sampling approaches are proposed and examined. The experimental evaluation of a real data set validates the feasibility of the proposed model, and also demonstrates its effectiveness.
Year
DOI
Venue
2014
10.1109/INFOCOM.2014.6848108
INFOCOM
Keywords
DocType
ISSN
fluid exchange,rating prediction scheme,human opinions,rating prediction,FluidRating,unknown ratings,time-evolving rating scheme,trusted computing,recommender systems,trust-based recommendation system,uniform aggregation,time-evolving,time-evolving formulation process,trust-based recommendation systems,Fluid dynamics theory,nonuniform aggregation,fluid dynamics
Conference
0743-166X
Citations 
PageRank 
References 
2
0.37
0
Authors
4
Name
Order
Citations
PageRank
Wenjun Jiang135624.25
jie wu232747.55
Guojun Wang31740144.41
Huanyang Zheng413617.00