Search results
1 – 2 of 2Kuo-Cheng Ting, Ruei-Ping Wang, Yi-Chung Chen, Don-Lin Yang and Hsi-Min Chen
Using social networks to identify users with traits similar to those of the target user has proven highly effective in the development of personalized recommendation systems…
Abstract
Purpose
Using social networks to identify users with traits similar to those of the target user has proven highly effective in the development of personalized recommendation systems. Existing methods treat all dimensions of user data as a whole, despite the fact that most of the information related to different dimensions is discrete. This has prompted researchers to adopt the skyline query for such search functions. Unfortunately, researchers have run into problems of instability in the number of users identified using this approach.
Design/methodology/approach
We thus propose the m-representative skyline queries to provide control over the number of similar users that are returned. We also developed an R-tree-based algorithm to implement the m-representative skyline queries.
Findings
By using the R-tree based algorithm, the processing speed of the m-representative skyline queries can now be accelerated. Experiment results demonstrate the efficacy of the proposed approach.
Originality/value
Note that with this new way of finding similar users in the social network, the performance of the personalized recommendation systems is expected to be enhanced.
Details