A New Method for Graph Queries Processing without Index Reconstruction on Dynamic Graph Databases
Автор: Hamed Dinari
Журнал: International Journal of Modern Education and Computer Science (IJMECS) @ijmecs
Статья в выпуске: 2 vol.9, 2017 года.
Бесплатный доступ
Graphs play notable role in daily life. For instance, they are used in variety fields such as social networks, malware detection, and biological networks. Graph data processing performed to extract useful information is known as graph mining. A critical field of graph mining is graph containment problem, in which all graphs containing the query are returned by a graph query q. Scanning the whole database (graph query as a subgraph) for a query is a time consuming process. To improve query performance, an inverted index is constructed on the graph database and then the query is performed based on the query. The problem in this process is that when a graph is added to or removed from a database, the inverted index must be reconstructed. The present study proposes a method in which index updating is not needed upon a change in the database. This feature enables simultaneous inverted index updating and querying. The assessment results showed optimum and satisfactory performance of the proposed method.
Graph query processing, Graph mining, Data mining, Dynamic graph database
Короткий адрес: https://sciup.org/15014946
IDR: 15014946
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