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3-HOP: a high-compression indexing scheme for reachability query
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International Conference on Management of Data archive
Proceedings of the 35th SIGMOD international conference on Management of data table of contents
Providence, Rhode Island, USA
SESSION: Research session 21: indexing table of contents
Pages 813-826  
Year of Publication: 2009
ISBN:978-1-60558-551-2
Authors
Ruoming Jin  Kent State University, Kent, OH, USA
Yang Xiang  Kent State University, Kent, OH, USA
Ning Ruan  Kent State University, Kent, OH, USA
David Fuhry  Kent State University, Kent, OH, USA
Sponsors
ACM: Association for Computing Machinery
SIGMOD: ACM Special Interest Group on Management of Data
Publisher
ACM  New York, NY, USA
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ABSTRACT

Reachability queries on large directed graphs have attracted much attention recently. The existing work either uses spanning structures, such as chains or trees, to compress the complete transitive closure, or utilizes the 2-hop strategy to describe the reachability. Almost all of these approaches work well for very sparse graphs. However, the challenging problem is that as the ratio of the number of edges to the number of vertices increases, the size of the compressed transitive closure grows very large. In this paper, we propose a new 3-hop indexing scheme for directed graphs with higher density. The basic idea of 3-hop indexing is to use chain structures in combination with hops to minimize the number of structures that must be indexed. Technically, our goal is to find a 3-hop scheme over dense DAGs (directed acyclic graphs) with minimum index size. We develop an efficient algorithm to discover a transitive closure contour, which yields near optimal index size. Empirical studies show that our 3-hop scheme has much smaller index size than state-of-the-art reachability query schemes such as 2-hop and path-tree when DAGs are not very sparse, while our query time is close to path-tree, which is considered to be one of the best reachability query schemes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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Collaborative Colleagues:
Ruoming Jin: colleagues
Yang Xiang: colleagues
Ning Ruan: colleagues
David Fuhry: colleagues