GraSS: Graph Structure Summarization

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GraSS: Graph Structure Summarization
Large graph databases are commonly collected and analyzed in numerous domains. For reasons related to either space efficiency or for privacy protection (e.g., in the case of social network graphs), it sometimes makes sense to replace the original graph with a summary, which removes certain details about the original graph topology. However, this summarization process leaves the database owner with the challenge of processing queries that are expressed in terms of the original graph, but are answered using the summary. In this paper, we propose a formal semantics for answering queries on summaries of graph structures. At its core, our formulation is based on a random worlds model. We show that important graph-structure queries (e.g., adjacency, degree, and eigenvector centrality) can be answered efficiently and in closed form using these semantics. Further, based on this approach to query answering, we formulate three novel graph partitioning/compression problems. We develop algorithms...
Kristen LeFevre, Evimaria Terzi
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where SDM
Authors Kristen LeFevre, Evimaria Terzi
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