Research and application on similarity search algorithm in graph database
图数据库中的相似性搜索算法研究与应用

Similarity search of graph database is a significant research subject. The graph similarity match belongs to the category of decision problem of graph isomorphism. That is NP complete problem. The traditional high-consuming approach has not been able to meet the contemporary needs of complex graph search. Additionally, because of the complexity and specificity of graph database, the existing optimization algorithm can not be applied directly to this field. Therefore, it is necessary to explore a more advanced graph similarity algorithm. This paper proposed a novel similarity search algorithm, which was based on index. That was, establishing a feature index though frequent structure in database. The algorithm could filter a large number of non-similar data sets effectively and accurately, thus avoiding the calculation of exact match. Finally, applied the algorithm to the chemical database. The experimental result demonstrates that the approach is effective and feasible.