class StrictSim[TLabel] extends GraphMatcher[TLabel]
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
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Instance Constructors
- new StrictSim(g: Graph[TLabel], q: Graph[TLabel], duals: GraphMatcher[TLabel])(implicit arg0: ClassTag[TLabel])
- g
the data graph G(V, E, l)
- q
the query graph Q(U, D, k)
Value Members
- final def !=(arg0: Any): Boolean
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- final def ##: Int
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- final def ==(arg0: Any): Boolean
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- val CHECK: Int
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- protected
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- GraphMatcher
- val LIMIT: Double
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- GraphMatcher
- val SELF_LOOPS: Boolean
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- protected
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- GraphMatcher
- final def asInstanceOf[T0]: T0
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- 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
- def clone(): AnyRef
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- protected[lang]
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- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- def countMappings(phi: Array[Set[Int]]): Pair
Count the number of mappings between query graph vertices 'u_i' and their sets of data graph vertices {v}, giving the number of distinct vertices and edges.
Count the number of mappings between query graph vertices 'u_i' and their sets of data graph vertices {v}, giving the number of distinct vertices and edges.
- phi
the set-valued mapping function
- Definition Classes
- GraphMatcher
- def disjoint(set1: Set[Int], set2: Set[Int]): Boolean
Determine whether two sets are disjoints, i.e., have an empty intersection.
Determine whether two sets are disjoints, i.e., have an empty intersection.
- set1
the first set
- set2
the second set
- Definition Classes
- GraphMatcher
- def dualFilter(phi: Array[Set[Int]], ball: Ball[TLabel]): 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)
- final def eq(arg0: AnyRef): Boolean
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- def equals(arg0: AnyRef): Boolean
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- 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
- def feasibleMatesW(): 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. This version handles query graph labels that have wildcards.
- Definition Classes
- GraphMatcher
- def filterGraph(phi: Array[Set[Int]]): Graph[TLabel]
Filter the data graph by consider only those vertices and edges which are part of feasible matches after performing initial dual simulation.
Filter 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 }
- Definition Classes
- GraphMatcher
- val gRange: Range
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- protected
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- GraphMatcher
- final def getClass(): Class[_ <: AnyRef]
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- def hashCode(): Int
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- final def isInstanceOf[T0]: Boolean
- Definition Classes
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- 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
- StrictSim → GraphMatcher
- def mappings2(): Map[Int, Array[Set[Int]]]
Return mapping results per ball.
- final def ne(arg0: AnyRef): Boolean
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- final def notify(): Unit
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- 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
- StrictSim → GraphMatcher
- val qRange: Range
- Attributes
- protected
- Definition Classes
- GraphMatcher
- def refine(phi: Array[Set[Int]]): Map[Int, Array[Set[Int]]]
Refine 'phi' using strict simulation to find mappings within balls.
Refine 'phi' using strict simulation to find mappings within balls.
- phi
the initial mapping after applying Dual to the whole graph
- def selectivityCriteria(qmet: GraphMetrics[TLabel]): 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.
- def showMappings(phi: Array[Set[Int]]): Unit
Show all mappings between query graph vertices 'u_i' and their sets of data graph vertices {v}.
Show all mappings between query graph vertices 'u_i' and their sets of data graph vertices {v}.
- phi
the set-valued mapping function
- Definition Classes
- GraphMatcher
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
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- def test(name: String, ans: Array[Set[Int]] = null): Array[Set[Int]]
Test the Graph Pattern Matcher.
- def toString(): String
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- final def wait(arg0: Long, arg1: Int): Unit
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- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
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- Deprecated