gPrune: A Constraint Pushing Framework for Graph Pattern Mining

• Main Authors: ZHU, Feida, YAN, Xifeng, HAN, Jiawei, YU, Philip S.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2007
• Subjects: Antimonotonicities; Pruning properties; Constraint theory; Data reduction; Data structures; Pattern recognition; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/901; https://ink.library.smu.edu.sg/context/sis_research/article/1900/viewcontent/gPrune_pp.pdf
• Institution: Singapore Management University

In graph mining applications, there has been an increasingly strong urge for imposing user-specified constraints on the mining results. However, unlike most traditional itemset constraints, structural constraints, such as density and diameter of a graph, are very hard to be pushed deep into the mini...