Large-scale frequent subgraph mining in MapReduce

  title={Large-scale frequent subgraph mining in MapReduce},
  author={Wenqing Lin and Xiaokui Xiao and Gabriel Ghinita},
  journal={2014 IEEE 30th International Conference on Data Engineering},
Mining frequent subgraphs from a large collection of graph objects is an important problem in several application domains such as bio-informatics, social networks, computer vision, etc. The main challenge in subgraph mining is efficiency, as (i) testing for graph isomorphisms is computationally intensive, and (ii) the cardinality of the graph collection to be mined may be very large. We propose a two-step filter-and-refinement approach that is suitable to massive parallelization within the… CONTINUE READING
Highly Cited
This paper has 53 citations. REVIEW CITATIONS


Publications citing this paper.
Showing 1-10 of 37 extracted citations

54 Citations

Citations per Year
Semantic Scholar estimates that this publication has 54 citations based on the available data.

See our FAQ for additional information.

Similar Papers

Loading similar papers…