Summarization Graph Indexing: Beyond Frequent Structure-Based Approach

Graph is an important data structure to model complex structural data, such as chemical compounds, proteins, and XML documents. Among many graph data-based applications, sub-graph search is a key problem, which is defined as given a query Q, retrieving all graphs containing Q as a sub-graph in the graph database. Most existing sub-graph search methods try to filter out false positives (graphs that are not possible in the results) as many as possible by indexing some frequent sub-structures in graph database, such as [20, 22, 4, 23]. However, due to ignoring the relationships between sub-structures, these methods still admit a high percentage of false positives. In this paper, we propose a novel concept, Summarization Graph, which is a complete graph and captures most topology information of the original graph, such as sub-structures and their relationships. Based on Summarization Graphs, we convert the filtering problem into retrieving objects with set-valued attributes. Moreover, w...

• Type: Conference
• Year: 2008
• Where: DASFAA
• Authors: Lei Zou, Lei Chen 0002, Huaming Zhang, Yansheng Lu, Qiang Lou
• Keywords: DASFAA 2008, Database, Graph Data-based Applications, Graph Database, Summarization Graphs