# Using Recurrent Neural Network for Learning Expressive Ontologies

Source: [Using Recurrent Neural Network for Learning Expressive Ontologies](<https://www.sota2.com/research/paper/68fa629b1e209131ce9fa210>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-28T13:56:32.011Z

Authors: Giulio Petrucci, Chiara Ghidini, Marco Rospocher

Published: 2016-07-14T12:45:07.000Z

## Abstract

Recently, Neural Networks have been proven extremely effective in many natural language processing tasks such as sentiment analysis, question answering, or machine translation. Aiming to exploit such advantages in the Ontology Learning process, in this technical report we present a detailed description of a Recurrent Neural Network based system to be used to pursue such goal.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/1607.04110>)

[PDF](<https://arxiv.org/pdf/1607.04110.pdf>)