Edge labeling schemes for graph data
Conference item
Goonetilleke, Oshini, Koutra, Danai, Sellis, Timos and Liao, Kewen. (2017). Edge labeling schemes for graph data. 29th International Conference on Scientific and Statistical Database Management. United States of America: Association for Computing Machinery. pp. 1 - 12 https://doi.org/10.1145/3085504.3085516
Authors | Goonetilleke, Oshini, Koutra, Danai, Sellis, Timos and Liao, Kewen |
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Abstract | Given a directed graph, how should we label both its outgoing and incoming edges to achieve better disk locality and support neighborhood-related edge queries? In this paper, we answer this question with edge-labeling schemes GrdRandom and FlipInOut, to label edges with integers based on the premise that edges should be assigned integer identifiers exploiting their consecutiveness to a maximum degree. |
Year | 2017 |
Journal | Proceedings of the 29th International Conference on Scientific and Statistical Database Management (SSDBM '17 ) |
Publisher | Association for Computing Machinery |
Digital Object Identifier (DOI) | https://doi.org/10.1145/3085504.3085516 |
Publisher's version | File Access Level Controlled |
Page range | 1 - 12 |
Research Group | Peter Faber Business School |
Place of publication | United States of America |
https://acuresearchbank.acu.edu.au/item/85948/edge-labeling-schemes-for-graph-data
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