Connected substructure similarity search

10 years 1 months ago
Connected substructure similarity search
Substructure similarity search is to retrieve graphs that approximately contain a given query graph. It has many applications, e.g., detecting similar functions among chemical compounds. The problem is challenging as even testing subgraph containment between two graphs is NP-complete. Hence, existing techniques adopt the filtering-and-verification framework with the focus on developing effective and efficient techniques to remove non-promising graphs. Nevertheless, existing filtering techniques may be still unable to effectively remove many “low” quality candidates. To resolve this, in this paper we propose a novel indexing technique, GrafD-Index, to index graphs according to their “distances” to features. We characterize a tight condition under which the distance-based triangular inequality holds. We then develop lower and upper bounding techniques that exploit the GrafD-Index to (1) prune non-promising graphs and (2) include graphs whose similarities are guaranteed to e...
Haichuan Shang, Xuemin Lin, Ying Zhang, Jeffrey Xu
Added 14 Aug 2010
Updated 14 Aug 2010
Type Conference
Year 2010
Authors Haichuan Shang, Xuemin Lin, Ying Zhang, Jeffrey Xu Yu, Wei Wang 0011
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