Modelling the generalised median correspondence through an edit distance.
Moreno-García, Carlos Francisco
MetadataShow full item record
MORENO-GARCÍA, C.F. and SERRATOSA, F. 2018. Modelling the generalised median correspondence through an edit distance. In Bai, X., Hancock, E., Ho, T., Wilson, R., Biggio, B. and Robles-Kelly, A. (eds.) Lecture notes in computer science, 11004: structural, syntactic and statistical pattern recognition: proceedings of the Joint International Association of Pattern Recognition (IAPR) international workshop on structural and syntactic pattern recognition and statistical techniques in pattern recognition (S+SSPR 2018), 17-19 August 2018, Beijing, China. Cham: Springer [online], pages 271-281. Available from: https://doi.org/10.1007/978-3-319-97785-0_26
On the one hand, classification applications modelled by structural pattern recognition, in which elements are represented as strings, trees or graphs, have been used for the last thirty years. In these models, structural distances are modelled as the correspondence (also called matching or labelling) between all the local elements (for instance nodes or edges) that generates the minimum sum of local distances. On the other hand, the generalised median is a well-known concept used to obtain a reliable prototype of data such as strings, graphs and data clusters. Recently, the structural distance and the generalised median has been put together to define a generalise median of matchings to solve some classification and learning applications. In this paper, we present an improvement in which the Correspondence edit distance is used instead of the classical Hamming distance. Experimental validation shows that the new approach obtains better results in reasonable runtime compared to other median calculation strategies.