svcR: An R Package for Support Vector Clustering improved with Geometric Hashing applied to Lexical Pattern Discovery

Nicolas Turenne (1)

1 INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

We present a new R package which takes a numerical matrix format as data input, and computes clusters using a support vector clustering method (SVC). We have implemented an original 2D-grid labeling approach to speed up cluster extraction. In this sense, SVC can be seen as an efficient cluster extraction if clusters are separable in a 2-D map. Secondly we showed that this SVC approach using a Jaccard-Radial base kernel can help to classify well enough a set of terms into ontological classes and help to define regular expression rules for information extraction in documents; our case study concerns a set of terms and documents about developmental and molecular biology.

Domaines: Informatique [cs]

Nicolas Turenne. svcR: An R Package for Support Vector Clustering improved with Geometric Hashing applied to Lexical Pattern Discovery. 2015. ⟨hal-03373979⟩