Title :
Measuring Similarity Based on Link Information: A Comparative Study
Author :
Hongyan Liu ; Jun He ; Dan Zhu ; Ling, Charles X. ; Xiaoyong Du
Author_Institution :
Res. Center for Contemporary Manage., Tsinghua Univ., Beijing, China
Abstract :
Measuring similarity between objects is a fundamental task in domains such as data mining, information retrieval, and so on. Link-based similarity measures have attracted the attention of many researchers and have been widely applied in recent years. However, most previous works mainly focus on introducing new link-based measures, and seldom provide theoretical as well as experimental comparisons with other measures. Thus, selecting the suitable measure in different situations and applications is difficult. In this paper, a comprehensive analysis and critical comparison of various link-based similarity measures and algorithms are presented. Their strengths and weaknesses are discussed. Their actual runtime performances are also compared via experiments on benchmark data sets. Some novel and useful guidelines for users to choose the appropriate link-based measure for their applications are discovered.
Keywords :
pattern clustering; link information; link-based similarity algorithms; link-based similarity measures; similarity measurement; Algorithm design and analysis; Approximation algorithms; Atmospheric measurements; Computational modeling; Current measurement; Data mining; Particle measurements; Link-based similarity; SimRank; clustering; random walk; similarity measures;
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
DOI :
10.1109/TKDE.2012.194