Abstract
The article presents the owlANT method, which allows us to associate a collection of short text messages with ontology. The trails were conducted on the collection of communications by Reuters (the so-called second collection). As the methodological base of the method, a swarm intelligence was used, namely the ant colony optimisation. The ants, moving between the ontological nodes [1][2], left their pheromone trace. As a result, some branches of relations - after some time in evolution - were marked more strongly than the others. On the basis of the intensity of the pheromone trace, one can formulate the strength of relations between the various associations, and - indirectly - also between the associated documents. As far as the authors know, no one has so far published research on the application of ACO to the development of similarity measure of text documents with the consideration of their meaning-related embedding in ontology. The authors refer to the work [3][4], in which the ACO was used for aggregation of concepts in ontology; however, both the purpose and the method were different in that case. The research described in the report will be continued to specify the similarity measures taking into consideration the distance in ontology obtained thanks to the evolutionary processing of the meaning of terms with the use of ACO.
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Czerniak, J.M., Dobrosielski, W., Zarzycki, H., Apiecionek, Ł. (2015). A Proposal of the New owlANT Method for Determining the Distance between Terms in Ontology. In: Filev, D., et al. Intelligent Systems'2014. Advances in Intelligent Systems and Computing, vol 323. Springer, Cham. https://doi.org/10.1007/978-3-319-11310-4_21
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DOI: https://doi.org/10.1007/978-3-319-11310-4_21
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