Semantic similarity network

A semantic similarity network (SSN) is a special form of semantic network.^[1] It is specially designed to represent concepts and their semantic similarity. The main contribution is the reduction of complexity for the calculation of semantic distances. Bendeck (2004, 2008) introduced the concept of semantic similarity networks (SSN) as the specialization of a semantic network to measure semantic similarity from ontological representations.^[2]

The concept is formally defined as a directed graph with concepts as nodes and semantic similarity relations as edges.^[3] The relationships are grouped into relation types. The concepts and relations contain attribute values to evaluate the semantic similarity^[4] between concepts. The semantic similarity relationships of the SSN represents (reduce/combine) several of the general relationships types of the standard Semantic network, reducing the complexity of the (normally, very large) network for calculations of semantics similarity.SSNs defines relation types as templates (and taxonomy of relations) for semantic similarity attributes that are common to relations of the same type. SSN representation allows propagation algorithms to the faster calculation of semantic similarities, including stop conditions within a specified threshold. This reduces the computation time and power required the calculation.

Implementations include genetic information handling.^[5]^[6]

References

^ R. H. Richens: "General program for mechanical translation between any two languages via an algebraic interlingua". Cambridge Language Research Unit. Mechanical Translation, November 1956; p. 37
^ Fawsy Bendeck, Three Fold "Ontology + Model + Instance (OMI) - Semantic Unification Process, In International Conference on Advances in Internet, Processing, System and Interdisciplinary Research (IPSI-2004), Stockholm, Sep 2004, ISBN 86-7466-1173.
^ Bendeck, F. (2008). WSM-P Workflow Semantic Matching Platform. Verlag Dr. Hut.
^ P. Resnik. Using Information Content to Evaluate Semantic Similarity in a Taxonomy. Proc. the 14th International Joint Conference on Artificial Intelligence, 448–453, 1995.
^ Jiang, R.; Gan, M.; He, P. (2011). "Constructing a gene semantic similarity network for the inference of disease genes". BMC Systems Biology. 5 (2): 2.
^ Guzzi, P. H.; Veltri, P.; Cannataro, M. (2013). "Thresholding of semantic similarity networks using a spectral graph-based technique". International Workshop on New Frontiers in Mining Complex Patterns. Cham: Springer. pp. 201–213.

[1] R. H. Richens: "General program for mechanical translation between any two languages via an algebraic interlingua". Cambridge Language Research Unit. Mechanical Translation, November 1956; p. 37

[2] Fawsy Bendeck, Three Fold "Ontology + Model + Instance (OMI) - Semantic Unification Process, In International Conference on Advances in Internet, Processing, System and Interdisciplinary Research (IPSI-2004), Stockholm, Sep 2004, ISBN 86-7466-1173.

[bendeck-3] Bendeck, F. (2008). WSM-P Workflow Semantic Matching Platform. Verlag Dr. Hut.

[4] P. Resnik. Using Information Content to Evaluate Semantic Similarity in a Taxonomy. Proc. the 14th International Joint Conference on Artificial Intelligence, 448–453, 1995.

[5] Jiang, R.; Gan, M.; He, P. (2011). "Constructing a gene semantic similarity network for the inference of disease genes". BMC Systems Biology. 5 (2): 2.

[6] Guzzi, P. H.; Veltri, P.; Cannataro, M. (2013). "Thresholding of semantic similarity networks using a spectral graph-based technique". International Workshop on New Frontiers in Mining Complex Patterns. Cham: Springer. pp. 201–213.

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