Semantic Graph Structure

A Semantic Graph Structure is a graph or a decision tree that are used to represent semantic relationships between terms.

• Context:
  • It (usually) consists of representing nodes as concepts (ontological terms, words, subwords) and the edges as semantic similarity score or semantic distance.
• Example(s)
  • an edge-weighted graph such as WordNet (Lin, 1998):

    .

  • a directed acyclic graph such a GO Graph (Pesquita et al, 2009):

    ,

  • a decision tree such as in Wu & Palmer (1994):

    

  • …
• Counter-Example(s):
  • a Flow Network,
  • an Undirected Graph.
• See: Semantic Similarity Measure, Graph-based Semantic Similarity Measure, Tree-based Semantic Similarity Measure, Vector-based Semantic Similarity Measure.

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References

2009

• (Pesquita et al., 2009 ) ⇒ Catia Pesquita, Daniel Faria, Andre O. Falcao, Phillip Lord, and Francisco M. Couto (2009). "Semantic Similarity in Biomedical Ontologies". In: PLoS Computational Biology 5(7): e1000443.

2008

• (Pesquita et al., 2008) &rArr Catia Pesquita, Daniel Faria, Hugo Bastos, Antonio EN Ferreira, Andre O Falcao, and Francisco M Couto (2008). "Metrics for GO based protein semantic similarity: a systematic evaluation". In: BMC Bioinformatics volume 9, Article number: S4.

1998

• (Lin, 1998) ⇒ Dekang Lin. (1998). “An Information-Theoretic Definition of Similarity.” In: Proceedings of the 15th International Conference on Machine Learning (ICML 1998).

1994

• (Wu & Palmer, 1994) ⇒ Zhibiao Wu, and Martha Palmer (1994). "Verb Semantics and Lexical Selection". In: arXiv preprint /abscmp-lg/9406033.

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