LooPings: a Look at Semantic Similarities

Semantic similarities is a cross-field research in Natural Language Processing and Ontologies with some possible fallouts in Artificial Intelligence. Formerly, similarities were computed following a syntactical treatment to support case-based reasoning. Textual similarities are now guided by semantic machineries, offering various ways to compute relatedness measures. In this paper, we present both a logical and a visual framework aiming to reason with them. For that reason, we introduced FLH±, a fragment of description logic underpinning the well-known lexical database Wordnet. We illustrated this framework with the path length relatedness, one of the historical similarity measures occurring in a taxonomy. The core of our framework orchestrates the computation of similarity scores supported by REVERB, STANFORD CORENLP and WORDNET:SIMILARITY APIs and interfaces global similarities in graphical way by positioning them on segments. We also depicted some experimental results to confront our computational framework with some empirical data.

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