GString: A Novel Approach for Efficient Search in Graph Databases

Graphs are widely used for modeling complicated data, including chemical compounds, protein interactions, XML documents, and multimedia. Information retrieval against such data can be formulated as a graph search problem, and finding an efficient solution to the problem is essential for many applications. A popular approach is to represent both graphs and queries on graphs by sequences, thus converting graph search to subsequence matching. State-of-the-art sequencing methods work at the finest granularity ? each node (or edge) in the graph will appear as an element in the resulting sequence. Clearly, such methods are not semantic conscious, and the resulting sequences are not only bulky but also prone to complexities arising from graph isomorphism and other problems in searching. In this paper, we introduce a novel sequencing method to capture the semantics of the underlying graph data. We find meaningful components in graph structures and use them as the most basic units in sequencin...

• Type: Conference
• Year: 2007
• Where: ICDE
• Authors: Haoliang Jiang, Haixun Wang, Philip S. Yu, Shuigeng Zhou
• Keywords: Database, Graph Isomorphism, Graph Search Methods, Graph Search Problem, ICDE 2007