Graph database is designed to store bidirectional relationships between
objects and facilitate the traversal process to extract a subgraph. However,
the subgraph matching process is an NP-Complete problem. Existing solutions to
this problem usually employ a filter-and-verification framework and a
divide-and-conquer method. The filter-and-verification framework minimizes the
number of inputs to the verification stage by filtering and pruning invalid
candidates as much as possible. Meanwhile, subgraph matching is performed on
the substructure decomposed from the larger graph to yield partial embedding.
Subsequently, the recursive traversal or set intersection technique combines
the partial embedding into a complete subgraph. In this paper, we first present
a comprehensive literature review of the state-of-the-art solutions. l2Match, a
subgraph isomorphism algorithm for small queries utilizing a Label-Pair Index
and filtering method, is then proposed and presented as a proof of concept.
Empirical experimentation shows that l2Match outperforms related
state-of-the-art solutions, and the proposed methods optimize the existing
algorithms.Comment: This short version of this article (6 pages) is accepted by ICEIC
202