Introduction to Neural Network based Approaches for Question Answering over Knowledge Graphs
arXiv:1907.09361
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.
arXiv commentPreprint, under review. The first four authors contributed equally to this paper, and should be regarded as co-first authors
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Cited by in corpus (12)
- QAnswer: Towards Question Answering Search over Websites
- Applications of knowledge graphs for food science and industry
- Knowledge Graph Question Answering using Graph-Pattern Isomorphism
- Knowledge Graph-based Question Answering with Electronic Health Records
- A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions
- Thrill-K Architecture: Towards a Solution to the Problem of Knowledge Based Understanding
- Question-Aware Memory Network for Multi-hop Question Answering in Human-Robot Interaction
- A Survey on Semantic Parsing from the perspective of Compositionality
- Distantly Supervised Question Parsing
- Complex Knowledge Base Question Answering: A Survey
- WebSRC: A Dataset for Web-Based Structural Reading Comprehension
- Question Answering over Knowledge Graphs with Neural Machine Translation and Entity Linking