• Aucun résultat trouvé

Statistical Machine Learning with Linked Data

N/A
N/A
Protected

Academic year: 2022

Partager "Statistical Machine Learning with Linked Data"

Copied!
1
0
0

Texte intégral

(1)

Statistical Machine Learning with Linked Data Talk Abstract

Volker Tresp1

Siemens CT, volker.tresp@siemens.com,

The size of the Linked Open Data (LOD) cloud is constantly increasing where the term Linked Data is used to describe a method of exposing, sharing, and connecting data via dereferenceable URIs on the Web. In this talk we explore the usefulness of statistical machine learning for LOD. Statistical machine learning has the chance of exploiting statistical regularities in the data that cannot easily be captured by logical statements and can handle contradictory, uncertain and missing data. In general, the data quality on LOD is varying: whereas LOD for the life sciences has reasonably good quality, other portions of the LOD cloud are not maintained as well and are still quite noisy. We present existing machine learning approaches to learning with LOD. We conclude that machine learning can be quite effective on LOD if the data quality fulfils some minimal quality requirements.

Références

Documents relatifs

In the picture below the effect of the capacity |F | is analyzed on the variance term, bias term and total excess risk, for a fixed dataset.. In particular there are two

The interpretation of the information cohomology in terms of machine learning and data analysis first relies on the definition of random variables as partition and of

Gaussian graphi- cal models (GGMs) [1–3], probabilistic Boolean networks (PBNs) [4–7], Bayesian networks (BNs) [8,9], differential equation based [10,11] and mutual information

If this picture is correct, and the present data do not contradict it, as it is possible to classify the combined dataset with 100% accuracy using a decision tree, then it is

Statistical Machine-Learning: framework + supervised ML, Pr Fabien MOUTARDE, Center for Robotics, MINES ParisTech, PSL, Nov.2019 1..

The slice selected for the response variable comes from the dataset House prices of the Scottish portal 5 with the temporal dimension fixed to 2012, the measure type fixed to mean,

The method allows substantially get rid of the main weakness of the auto-tuning methodology, namely, significantly ac- celerate the search for an optimal program

Only in case of out- of-vocabulary source words (OOVs), which are not part of the available source language vocabulary and therefore cannot be translated by the system, approaches