Language Models (LMs) and Knowledge Graphs (KGs) are both active research areas in Machine Learning and Semantic Web. While LMs have brought great improvements for many downstream tasks on their own, they are often combined with KGs providing additionally aggregated, well structured knowledge. Usually, this is done by leveraging KGs to improve LMs. But what happens if we turn this around and use LMs to improve KGs?
Description
LM4KG: Improving Common Sense Knowledge Graphs with Language Models | SpringerLink
%0 Conference Paper
%1 omeliyanenko2020lm4kg
%A Omeliyanenko, Janna
%A Zehe, Albin
%A Hettinger, Lena
%A Hotho, Andreas
%B The Semantic Web -- ISWC 2020
%C Cham
%D 2020
%E Pan, Jeff Z.
%E Tamma, Valentina
%E d'Amato, Claudia
%E Janowicz, Krzysztof
%E Fu, Bo
%E Polleres, Axel
%E Seneviratne, Oshani
%E Kagal, Lalana
%I Springer International Publishing
%K 2020 graph kg knowledge language lm model myown nlp selected semantic
%P 456--473
%T LM4KG: Improving Common Sense Knowledge Graphs with Language Models
%U https://www.informatik.uni-wuerzburg.de/datascience/news/single/news/our-paper-lm4kg-improving-common-sense-knowledge-graphs-with-language-models-has-been-presented-a/
%X Language Models (LMs) and Knowledge Graphs (KGs) are both active research areas in Machine Learning and Semantic Web. While LMs have brought great improvements for many downstream tasks on their own, they are often combined with KGs providing additionally aggregated, well structured knowledge. Usually, this is done by leveraging KGs to improve LMs. But what happens if we turn this around and use LMs to improve KGs?
%@ 978-3-030-62419-4
@inproceedings{omeliyanenko2020lm4kg,
abstract = {Language Models (LMs) and Knowledge Graphs (KGs) are both active research areas in Machine Learning and Semantic Web. While LMs have brought great improvements for many downstream tasks on their own, they are often combined with KGs providing additionally aggregated, well structured knowledge. Usually, this is done by leveraging KGs to improve LMs. But what happens if we turn this around and use LMs to improve KGs?},
added-at = {2021-01-24T18:31:20.000+0100},
address = {Cham},
author = {Omeliyanenko, Janna and Zehe, Albin and Hettinger, Lena and Hotho, Andreas},
biburl = {https://www.bibsonomy.org/bibtex/2f24522aac1d51bace861cd03d4fb7cf9/hotho},
booktitle = {The Semantic Web -- ISWC 2020},
description = {LM4KG: Improving Common Sense Knowledge Graphs with Language Models | SpringerLink},
editor = {Pan, Jeff Z. and Tamma, Valentina and d'Amato, Claudia and Janowicz, Krzysztof and Fu, Bo and Polleres, Axel and Seneviratne, Oshani and Kagal, Lalana},
interhash = {417fb85b2e86797f00438d569a1a3e46},
intrahash = {f24522aac1d51bace861cd03d4fb7cf9},
isbn = {978-3-030-62419-4},
keywords = {2020 graph kg knowledge language lm model myown nlp selected semantic},
pages = {456--473},
publisher = {Springer International Publishing},
timestamp = {2021-05-12T08:30:53.000+0200},
title = {LM4KG: Improving Common Sense Knowledge Graphs with Language Models},
url = {https://www.informatik.uni-wuerzburg.de/datascience/news/single/news/our-paper-lm4kg-improving-common-sense-knowledge-graphs-with-language-models-has-been-presented-a/},
year = 2020
}