Packages

class StrictSim extends GraphMatcher

The 'StrictSim' class provides an implementation for strict simulation graph pattern matching. This version uses DualSim.

See also

hipore.com/ijbd/2014/IJBD%20Vol%201%20No%201%202014.pdf

Linear Supertypes
GraphMatcher, AnyRef, Any
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Instance Constructors

  1. new StrictSim(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 a graph pattern matching algorithm to find subgraphs of data graph 'g' that isomorphically match query graph 'q'.

    Apply a graph pattern matching 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
    GraphMatcher
  2. def calculateBallDiameterMetrics(balls: Map[Int, Ball]): Statistic

    Calculate statistics (e.g., min, max, average diameter and standard deviation) on the balls left after post-processing.

    Calculate statistics (e.g., min, max, average diameter and standard deviation) on the balls left after post-processing.

    balls

    mappings from a center vertex to the Ball B(Graph, Center, Radius)

  3. def calculateTotalEdges(g: Graph, balls: Map[Int, Ball], matchCenters: Set[Int]): Int

    Count distinct edges left after post processing.

    Count distinct edges left after post processing.

    g

    the data graph G(V, E, l)

    balls

    mappings from a center vertex to the Ball B(Graph, Center, Radius)

    matchCenters

    set of all vertices which are considered as center

  4. def calculateTotalVertices(): Int

    Count distinct vertices left after post processing.

  5. 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
  6. def dualFilter(phi: Array[Set[Int]], ball: Ball): Array[Set[Int]]

    Perform dual simulation onto the ball.

    Perform dual simulation onto the ball.

    phi

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

    ball

    the Ball B(Graph, Center, Radius)

  7. 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
  8. def filterGraph(phi: Array[Set[Int]]): Graph

    Prune the data graph by consider only those vertices and edges which are part of feasible matches after performing initial dual simulation.

    Prune the data graph by consider only those vertices and edges which are part of feasible matches after performing initial dual simulation.

    phi

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

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

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

    Apply the Strict Graph Simulation 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
    StrictSimGraphMatcher
  10. def mappings2(): Map[Int, Array[Set[Int]]]

    Return mapping results per ball.

  11. 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
  12. def prune(phi: Array[Set[Int]]): Array[Set[Int]]

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

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

    phi

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

    Definition Classes
    StrictSimGraphMatcher
  13. def selectivityCriteria(qmet: GraphMetrics): Int

    Return the vertex from an array of central vertices, those which have highest 'ch' set size and lowest frequency of label in the query graph, i.e., highest ratio.

  14. 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
  15. 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