Packages

class GraphSimIso extends GraphMatcher

The GraphSimIso object provides an implementation for Subgraph Isomorphism that uses an adjacency set version of Ullmann's Algorithm.

Linear Supertypes
GraphMatcher, AnyRef, Any
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  1. GraphSimIso
  2. GraphMatcher
  3. AnyRef
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Instance Constructors

  1. new GraphSimIso(g: Graph, q: Graph)

    g

    the data graph G(V, E, l)

    q

    the query graph Q(U, D, k)

Value Members

  1. def bijections(): Set[Array[Int]]

    Apply the Ullmann's Subgraph Isomorphism algorithm to find subgraphs of data graph 'g' that isomorphically match query graph 'q'.

    Apply the Ullmann's Subgraph Isomorphism algorithm to find subgraphs of data graph 'g' that isomorphically match query graph 'q'. These are represented by a set of single-valued bijections {'psi'} where each 'psi' function maps each query graph vertex 'u' to a data graph vertices 'v'.

    Definition Classes
    GraphSimIso → GraphMatcher
  2. def disjoint(set1: Set[Int], set2: Set[Int]): Boolean

    Determine whether two sets are disjoint, i.e., have an empty intersection.

    Determine whether two sets are disjoint, i.e., have an empty intersection.

    set1

    the first set

    set2

    the second set

    Definition Classes
    GraphMatcher
  3. def feasibleMates(): Array[Set[Int]]

    Create an initial array of feasible mappings 'phi' from each query vertex 'u' to the corresponding set of data graph vertices '{v}' whose label matches 'u's.

    Create an initial array of feasible mappings 'phi' from each query vertex 'u' to the corresponding set of data graph vertices '{v}' whose label matches 'u's.

    Definition Classes
    GraphMatcher
  4. def getMatches(): Int

    Get the count of the number of matches.

  5. def makeOrder(): Array[Int]

    Establish a vertex order from largest to smallest adjacency set ('ch') size.

  6. def mappings(): Array[Set[Int]]

    Apply a graph pattern matching algorithm to find the mappings from the query graph 'q' to the data graph 'g'.

    Apply a graph pattern matching algorithm to find the mappings from the query graph 'q' to the data graph 'g'. These are represented by a multi-valued function 'phi' that maps each query graph vertex 'u' to a set of data graph vertices '{v}'.

    Definition Classes
    GraphMatcher
  7. def overlaps(set1: Set[Int], set2: Set[Int]): Boolean

    Determine whether two sets overlap, i.e., have a non-empty intersection.

    Determine whether two sets overlap, i.e., have a non-empty intersection.

    set1

    the first set

    set2

    the second set

    Definition Classes
    GraphMatcher
  8. def prune(phi: Array[Set[Int]]): Array[Set[Int]]

    The 'prune' is not needed, pruning is delegated to incorporated graph simulation algorithm.

    The 'prune' is not needed, pruning is delegated to incorporated graph simulation algorithm.

    phi

    array of mappings from a query vertex u_q to { graph vertices v_g }

    Definition Classes
    GraphSimIso → GraphMatcher
  9. def showMappings(phi: Array[Set[Int]]): Unit

    Show the mappings between a query graph vertex u and a set of data graph vertices {v}.

    Show the mappings between a query graph vertex u and a set of data graph vertices {v}.

    phi

    the set-valued mapping function

    Definition Classes
    GraphMatcher
  10. def test(name: String, ans: Array[Set[Int]] = null): Unit

    Test the graph pattern matcher.

    Test the graph pattern matcher.

    name

    the name of graph pattern matcher

    ans

    the correct answer

    Definition Classes
    GraphMatcher