slib.sml.sm.core.measures.graph.pairwise.dag.edge_based
Class Sim_pairwise_DAG_edge_Pekar_Staab_2002

java.lang.Object
  extended by slib.sml.sm.core.measures.graph.pairwise.dag.edge_based.Sim_DAG_edge_abstract
      extended by slib.sml.sm.core.measures.graph.pairwise.dag.edge_based.Sim_pairwise_DAG_edge_Pekar_Staab_2002
All Implemented Interfaces:
Sim_Pairwise_DAG, Sim_Pairwise

public class Sim_pairwise_DAG_edge_Pekar_Staab_2002
extends Sim_DAG_edge_abstract

Pekar V, Staab S: Taxonomy learning: factoring the structure of a taxonomy into a semantic classification decision. In COLING ’02 Proceedings of the 19th international conference on Computational linguistics. Association for Computational Linguistics; 2002, 2:1–7.

Author:
Harispe Sébastien

Constructor Summary
Sim_pairwise_DAG_edge_Pekar_Staab_2002()
           
 
Method Summary
 boolean isSymmetric()
           
 double sim(double sp_mrca_root, double sp_a_mrca, double sp_b_mrca)
          Compute the semantic similarity considering the given parameters.
 double sim(org.openrdf.model.URI a, org.openrdf.model.URI b, SM_Engine c, SMconf conf)
          Compute the semantic similarity of the pair of concepts/classes.
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

Sim_pairwise_DAG_edge_Pekar_Staab_2002

public Sim_pairwise_DAG_edge_Pekar_Staab_2002()
Method Detail

sim

public double sim(org.openrdf.model.URI a,
                  org.openrdf.model.URI b,
                  SM_Engine c,
                  SMconf conf)
           throws slib.utils.ex.SLIB_Ex_Critic
Description copied from interface: Sim_Pairwise
Compute the semantic similarity of the pair of concepts/classes.

Parameters:
a - the first concept/class
b - the second concept/class
c - the engine used to access information required by the measures
conf - the configuration to consider
Returns:
the similarity between the pair of concept/class.
Throws:
slib.utils.ex.SLIB_Ex_Critic

sim

public double sim(double sp_mrca_root,
                  double sp_a_mrca,
                  double sp_b_mrca)
Compute the semantic similarity considering the given parameters. The MRCA corresponds to the Most Recent Ancestor.

Parameters:
sp_mrca_root - shortest path from the MRCA to the root
sp_a_mrca - shortest path from the A to the MRCA
sp_b_mrca - shortest path from the B to the MRCA
Returns:
the semantic similarity

isSymmetric

public boolean isSymmetric()


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