Abstract
Many indexes have been designed to solve the problem of the point-to-point distance query on big graphs. In this paper, we design an incremental updating method for the index construction on dynamic graphs. The results show that the method is much time-saving compared with the way of index reconstruction. We also propose an exact method for distance labeling focused on undirected unweighted dense graphs. A kind of tight substructure named clique commonly exists in some dense graphs, such as social networks and communication networks. We take advantage of the cliques to compress the index. The experiments show that the technique can save index space and bring about comparable query time.
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This paper is partly supported by the NSFC under grant No. 61433019.
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Li, P., Xie, X., Jin, H., Chen, H., Ke, X. (2016). Optimizational Methods for Index Construction on Big Graphs. In: Wang, G., Han, Y., MartÃnez Pérez, G. (eds) Advances in Services Computing. APSCC 2016. Lecture Notes in Computer Science(), vol 10065. Springer, Cham. https://doi.org/10.1007/978-3-319-49178-3_23
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DOI: https://doi.org/10.1007/978-3-319-49178-3_23
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