ASSG: adaptive structural summary for RDF graph data
Haiwei Zhang, Yuanyuan Duan, Xiaojie Yuan, Ying Zhang · 2014
Abstract. RDF is considered to be an important data model for Seman-tic Web as a labeled directed graph. Querying in massive RDF graph data is known to be hard. In order to reduce the data size, we present ASSG, an Adaptive Structural Summary for RDFGraph data by bisimulations between nodes. ASSG compresses only the part of the graph related to queries. Thus ASSG contains less nodes and edges than existing work. More importantly, ASSG has the adaptive ability to adjust its structure according to the updating query graphs. Experimental results show that ASSG can reduce graph data with the ratio 85 % in average, higher than that of existing work.