# Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs

arXiv: https://arxiv.org/abs/1907.09361 · HTML: https://mlsanity.com/paper/1907.09361/

## Key facts

- Cited by 15 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Jul 2019.

## Built on by (most cited first, 15 of 15)

- [Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering](https://mlsanity.com/paper/2306.04136/) (2023)
- [WebSRC: A Dataset for Web-Based Structural Reading Comprehension](https://mlsanity.com/paper/2101.09465/) (2021)
- [A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions](https://mlsanity.com/paper/2105.11644/) (2021)
- [Complex Knowledge Base Question Answering: A Survey](https://mlsanity.com/paper/2108.06688/) (2021)
- [Neural Approaches to Conversational Information Retrieval](https://mlsanity.com/paper/2201.05176/) (2022)
- [DBLP-QuAD: A Question Answering Dataset over the DBLP Scholarly Knowledge Graph](https://mlsanity.com/paper/2303.13351/) (2023)
- [Knowledge Graph Question Answering using Graph-Pattern Isomorphism](https://mlsanity.com/paper/2103.06752/) (2021)
- [Grounding Dialogue Systems via Knowledge Graph Aware Decoding with Pre-trained Transformers](https://mlsanity.com/paper/2103.16289/) (2021)
- [Applications of knowledge graphs for food science and industry](https://mlsanity.com/paper/2107.05869/) (2021)
- [Question Answering over Knowledge Graphs with Neural Machine Translation and Entity Linking](https://mlsanity.com/paper/2107.02865/) (2021)
- [Question-Aware Memory Network for Multi-hop Question Answering in Human-Robot Interaction](https://mlsanity.com/paper/2104.13173/) (2021)
- [Semantic Parsing for Question Answering over Knowledge Graphs](https://mlsanity.com/paper/2401.06772/) (2023)
- [Towards Collaborative Question Answering: A Preliminary Study](https://mlsanity.com/paper/2201.09708/) (2022)
- [Thrill-K Architecture: Towards a Solution to the Problem of Knowledge Based Understanding](https://mlsanity.com/paper/2303.12084/) (2023)
- [HG-RAG: Hierarchy-Guided Retrieval-Augmented Generation for Structured Knowledge Graphs](https://mlsanity.com/paper/2607.14095/) (2026)

## Abstract (arXiv)

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.