Frequent Submap Discovery

Gosselin S., Damiand G., Solnon C.

Proc. of 22nd Symposium on Combinatorial Pattern Matching (CPM)
Lecture Notes in Computer Science 6661, pages 429-440, June 2011, Palermo, Italy

Abstract: Combinatorial maps are nice data structures for modeling the topology of nD objects subdivided in cells (e.g., vertices, edges, faces, volumes, ...) by means of incidence and adjacency relationships between these cells. In particular, they can be used to model the topology of plane graphs. In this paper, we describe an algorithm, called mSpan, for extracting patterns which occur frequently in a database of maps. We experimentally compare mSpan with gSpan on a synthetic database of randomly generated 2D and 3D maps. We show that gSpan does not extract the same patterns, as it only considers adjacency relationships between cells. We also show that mSpan exhibits nicer scale-up properties when increasing map sizes or when decreasing frequency.

Keywords: Combinatorial Map; Frequent submap; mSpan; gSpan.

BibTex references

@InProceedings{GDS11,
      author = {Gosselin, S. and Damiand, G. and Solnon, C.},
      title = {Frequent Submap Discovery},
      booktitle = {Proc. of 22nd Symposium on Combinatorial Pattern Matching (CPM)},
      series = {Lecture Notes in Computer Science},
      publisher = {Springer Berlin/Heidelberg},
      volume = {6661},
      pages = {429-440},
      month = {June},
      year = {2011},
      address = {Palermo, Italy},
      keywords = {Combinatorial Map; Frequent submap; mSpan; gSpan.},
      url = {https://doi.org/10.1007/978-3-642-21458-5_36}
}

Guillaume Damiand

Frequent Submap Discovery

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BibTex references

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