Link Prediction of Artificial Intelligence Concepts using Low Computational Power
Abstract
This paper presents an approach proposed for the Science4cast 2021 competition, organized by the Institute of Advanced Research in Artificial Intelligence, whose main goal was to predict the likelihood of future associations between machine learning concepts in a semantic network. The developed methodology corresponds to a solution for a scenario of availability of low computational power only, exploiting the extraction of low order topological features and its incorporation in an optimized classifier to estimate the degree of future connections between the nodes. The reasons that motivated the developed methodologies will be discussed, as well as some results, limitations and suggestions of improvements.
Cite
@article{arxiv.2202.03393,
title = {Link Prediction of Artificial Intelligence Concepts using Low Computational Power},
author = {Francisco Valente},
journal= {arXiv preprint arXiv:2202.03393},
year = {2022}
}
Comments
Solution awarded a special prize in the Science4cast 2021 competition. Presented and published in the IEEE Big Data 2021 conference. Minor text improvements and typos corrected from the published version