A. Pipitone, M. C. Campisi, R. Pirrone

An A* based semantic tokenizer for increasing the performance of semantic applications

Natural Language Processing Artificial Intelligence

Semantic Applications (SAs) makes use of ontologies and their performance can depend on the syntactic labels of the modeled entities, even if several approaches have been devised to formalize ontologies, no formal approaches have been devised for naming their constituents, which look as long word concatenations without any particular separation. We present a novel semantic tokenizer that finds the sub-words through an application of the A* based search algorithm, the A functions rely on a set of linguistic criteria and on the meta-cognitive perspective of the activity of reading.

This article is authored also by Synbrain data scientists and collaborators. READ THE FULL ARTICLE