Pairwise Semantic Similarity Measure

From GM-RKB
(Redirected from Pairwise SSM)
Jump to navigation Jump to search

A Pairwise Semantic Similarity Measure is a Topological Semantic Similarity Measure that calculates similarities between two ontological instances by combining the semantic similarities of the concepts that they represent.



References

2021

  • (Wikipedia, 2021) ⇒ https://en.wikipedia.org/wiki/Semantic_similarity#Topological_similarity Retrieved:2021-8-7.
    • There are essentially two types of approaches that calculate topological similarity between ontological concepts:
      • Edge-based: which use the edges and their types as the data source;
      • Node-based: in which the main data sources are the nodes and their properties.
    • Other measures calculate the similarity between ontological instances:
      • Pairwise: measure functional similarity between two instances by combining the semantic similarities of the concepts they represent
      • Groupwise: calculate the similarity directly not combining the semantic similarities of the concepts they represent

2009

Measure Approach Techniques Term Comparison
Lord et al. (2003) All pairs Average Resnik/Lin/Jiang
Sevilla et al. (2005) All pairs Maximum Resnik/Lin/Jiang
Riensche et al., (2007, XOA) All pairs Maximum XOA
Azuaje et al. (2005) Best pairs Average Resnik/Lin/Jiang
Couto et al. (2005) Best pairs Average GraSM+(Resnik/Lin/Jiang)
Schlicker et al. (2006, funSim) Best pairs Average simRel
Wang et al. (2007) Best pairs Average Wang
Tao et al. (2007) (ITSS) Best pairs Average Min. threshold Lin
Pozo et al. (2008) Best pairs Average Pozo
Lei et al. (2006) All pairs Best pairsa Average Max, Sum Depth of LCA
Table 2: Summary of pairwise approaches.

aLei et. al also consider exact matches only.

2008

2007a

2007b

2007c

2006a

2006b

2005a

2005b

2005c

2004

2003