Synonyms
Definition
Consider a data stream A = 〈a 1, a 2, … , a m 〉 where each data item a k ∈ [n] × [n]. Such a stream naturally defines an undirected, unweighted graph G = (V, E) where
Graph mining on streams is concerned with estimating properties of G, or finding patterns within G, given the usual constraints of the data-stream model, i.e., sequential access to A and limited memory. However, there are the following common variants.
Multi-Pass Models
It is common in graph mining to consider algorithms that may take more than one pass over the stream. There has also been work in the W-Stream model in which the algorithm is allowed to write to the stream during each pass [9]. These annotationscan then be...
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
This is a preview of subscription content, log in via an institution.
Recommended Reading
Aggarwal G, Datar M, Rajagopalan S, Ruhl M. On the streaming model augmented with a sorting primitive. In: IEEE symposium on foundations of computer science. 2004. p. 540–9.
Bar-Yossef Z, Kumar R, Sivakumar D. Reductions in streaming algorithms, with an application to counting triangles in graphs. In: ACM-SIAM symposium on discrete algorithms. 2002. p. 623–32.
Buchsbaum AL, Giancarlo R, Westbrook J. On finding common neighborhoods in massive graphs. Theor Comput Sci. 2003;1–3(299):707–18.
Buriol LS, Frahling G, Leonardi S, Marchetti-Spaccamela A, Sohler C. Counting triangles in data streams. In: Proceedings of the 25th ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems. 2006. p. 253–62.
Chakrabarti A, Cormode G, McGregor A. A near-optimal algorithm for computing the entropy of a stream. In: ACM-SIAM symposium on discrete algorithms. 2007. p. 328–35.
Cormode G, Muthukrishnan S. Space efficient mining of multigraph streams. In: Proceedings of the 24th ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems. 2005. p. 271–82.
Das Sarma A, Gollapudi S, Panigrahy R. Estimating PageRank on graph streams. In: Proceedings of the 27th ACM SIGACT-SIGMOD-SIGART symposium on principles of database systems. 2008. p. 69–78.
Demetrescu C, Escoffier B, Moruz G, Ribichini A. Adapting parallel algorithms to the w-stream model, with applications to graph problems. In: Mathematical foundations of computer science. 2007.p. 194–205.
Demetrescu C, Finocchi I, Ribichini A. Trading off space for passes in graph streaming problems. In: ACM-SIAM symposium on discrete algorithms. 2006. p. 714–23.
Elkin M. Streaming and fully dynamic centralized algorithms for constructing and maintaining sparse spanners. In: International colloquium on automata, languages and programming. 2007. p. 716–27.
Elkin M, Zhang J. Efficient algorithms for constructing (1 + ε, β)-spanners in the distributed and streaming models. Distrib Comput. 2006;18(5):375–85.
Feigenbaum J, Kannan S, McGregor A, Suri S, Zhang J. Graph distances in the data-stream model. SIAM J Comput. 2008;38(5):1708–27.
Feigenbaum J, Kannan S, McGregor A, Suri S, Zhang J. On graph problems in a semi-streaming model. Theor Comput Sci. 2005;348(2–3):207–16.
Ganguly S, Saha B. On estimating path aggregates over streaming graphs. In: International symposium on algorithms and computation. 2006. p. 163–72.
Henzinger MR, Raghavan P, Rajagopalan S. Computing on data streams. In: External memory algorithms. 1999. p. 107–18.
McGregor A. Finding graph matchings in data streams. In: APPROX-RANDOM. 2005. p. 170–81.
Muthukrishnan S. Data streams: algorithms and applications. Found Trends Theor Comput Sci. 2005;1(2)
Zelke M. k-connectivity in the semi-streaming model. CoRR, cs/0608066. 2006.
Zelke M. Weighted matching in the semi-streaming model. In: Proceedings of the symposium on theoretical aspects of computer science. 2008.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Section Editor information
Rights and permissions
Copyright information
© 2016 Springer Science+Business Media LLC
About this entry
Cite this entry
McGregor, A. (2016). Graph Mining on Streams. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_184-2
Download citation
DOI: https://doi.org/10.1007/978-1-4899-7993-3_184-2
Received:
Accepted:
Published:
Publisher Name: Springer, New York, NY
Online ISBN: 978-1-4899-7993-3
eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering