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Managing and Mining Large Graphs: Systems and Implementations

Summary: Tutorial-style survey of large-graph management and mining systems, noting the lack of a standard graph stack and the prevalence of ad-hoc algorithms. Explores architectural constraints, programming models, and goals for a general-purpose graph system, reviewing representative systems and design perspectives across applications. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4559
Venue
SIGMOD
Year
2012
Pagerank
5.4737941e-05
Overall Rank
5,504 | 61.72%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
1,066 Probase: A Probabilistic Taxonomy for Text Understanding 2012 SIGMOD 0.0001433416
1,675 A Distributed Graph Engine for Web Scale RDF Data 2013 VLDB 0.00010947606
4,921 Efficient Cohesive Subgraphs Detection in Parallel 2014 SIGMOD 5.8237536e-05
11,736 Declarative and distributed graph analytics with GRADOOP 2018 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
4 Pregel: A System for Large-Scale Graph Processing 2010 SIGMOD 0.0019005923
651 Efficient Subgraph Matching on Billion Node Graphs 2012 VLDB 0.00018648572
1,066 Probase: A Probabilistic Taxonomy for Text Understanding 2012 SIGMOD 0.0001433416
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