Searching substructures with superimposed distance

Xifeng Yan, Feida Zhu, Jiawei Han, Gabrielle Dawn Allen

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Efficient indexing techniques have been developed for the exact and approximate substructure search in large scale graph databases. Unfortunately, the retrieval problem of structures with categorical or geometric distance constraints is not solved y et. In this paper, we develop a method called PIS (Partition-based Graph Index and Search) to support similarity search on substructures with superimposed distance constraints. PIS selects discriminative fragments in a query graph and uses an index to prune the graphs that violate the distance constraints. We identify a criterion to distinguish the selectivity of fragments in multiple graphs and develop a partition method to obtain a set of highly selective fragments, which is able to improve the pruning performance. Experimental results show that PIS is effective in processing real graph queries.

Original languageEnglish (US)
Title of host publicationProceedings of the 22nd International Conference on Data Engineering, ICDE '06
Number of pages1
StatePublished - 2006
Event22nd International Conference on Data Engineering, ICDE '06 - Atlanta, GA, United States
Duration: Apr 3 2006Apr 7 2006

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627


Other22nd International Conference on Data Engineering, ICDE '06
Country/TerritoryUnited States
CityAtlanta, GA

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Information Systems


Dive into the research topics of 'Searching substructures with superimposed distance'. Together they form a unique fingerprint.

Cite this