Machine Learning

Irion makes use of several Machine Learning, techniques, such as supervised learning, unsupervised learning, and transduction. These techniques are usually combined with natural language technology, and with formal concept analysis, information extraction and simplex rule-based deduction to achieve the envisaged goals in solutions for customers. Particularly the supervised learning is used for our classification system, but here it is combined with a special brand of computational linguistics, namely annotated and normalised corpus statistics, and domain knowledge from thesauruses, other controlled vocabularies, and semantic networks.

Irion developed its own special brand of combined technologies to achieve the maximum performace of the classification system, that not only outperforms most of the classifications systems in the world, when applied in out-of-laboratory, ‘real-life’ situations, but also requires significantly less effort to build solutions.

A spectacular and recent example of this is the IPTC classifier for both Italian and Spanisgh which we developed recently with our partner LexisNexis in just three months.