Question answering has emerged as an intuitive way of querying structured data sources, and has attracted significant advancements over the years. In this article, we provide an overview over these recent advancements, focusing on neural network based question answering systems over knowledge graphs. We introduce readers to the challenges in the tasks, current paradigms of approaches, discuss notable advancements, and outline the emerging trends in the field. Through this article, we aim to provide newcomers to the field with a suitable entry point, and ease their process of making informed decisions while creating their own QA system.
%0 Journal Article
%1 Chakraborty2019-ro
%A Chakraborty, Nilesh
%A Lukovnikov, Denis
%A Maheshwari, Gaurav
%A Trivedi, Priyansh
%A Lehmann, Jens
%A Fischer, Asja
%D 2019
%I arXiv
%K
%T Introduction to neural network based approaches for question answering over knowledge graphs
%X Question answering has emerged as an intuitive way of querying structured data sources, and has attracted significant advancements over the years. In this article, we provide an overview over these recent advancements, focusing on neural network based question answering systems over knowledge graphs. We introduce readers to the challenges in the tasks, current paradigms of approaches, discuss notable advancements, and outline the emerging trends in the field. Through this article, we aim to provide newcomers to the field with a suitable entry point, and ease their process of making informed decisions while creating their own QA system.
@article{Chakraborty2019-ro,
abstract = {Question answering has emerged as an intuitive way of querying structured data sources, and has attracted significant advancements over the years. In this article, we provide an overview over these recent advancements, focusing on neural network based question answering systems over knowledge graphs. We introduce readers to the challenges in the tasks, current paradigms of approaches, discuss notable advancements, and outline the emerging trends in the field. Through this article, we aim to provide newcomers to the field with a suitable entry point, and ease their process of making informed decisions while creating their own QA system.},
added-at = {2024-09-10T11:56:37.000+0200},
author = {Chakraborty, Nilesh and Lukovnikov, Denis and Maheshwari, Gaurav and Trivedi, Priyansh and Lehmann, Jens and Fischer, Asja},
biburl = {https://puma.scadsai.uni-leipzig.de/bibtex/2b23dbbe6c5f0974aa3675b1f098ec4a0/scadsfct},
interhash = {b060198e54838e9eebdf3da2d89b4e30},
intrahash = {b23dbbe6c5f0974aa3675b1f098ec4a0},
keywords = {},
publisher = {arXiv},
timestamp = {2024-09-10T15:15:57.000+0200},
title = {Introduction to neural network based approaches for question answering over knowledge graphs},
year = 2019
}
