Learning from String Sequences

arXiv:2405.06301v1 Announce Type: new
Abstract: The Universal Similarity Metric (USM) has been demonstrated to give practically useful measures of "similarity" between sequence data. Here we have used the USM as an alternative distance metric in a K-Nearest Neighbours (K-NN) learner to allow effective pattern recognition of variable length sequence data. We compare this USM approach with the commonly used string-to-word vector approach. Our experiments have used two data sets of divergent domains: (1) spam email filtering and (2) protein subcellular …

abstract alternative arxiv cs.ai cs.ce cs.cl cs.cv cs.lg data pattern pattern recognition recognition string type universal