CLAILGJul 22, 2019

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

arXiv:1907.09361v156 citations
Originality Synthesis-oriented
AI Analysis

It serves as an introductory guide for researchers new to QA over knowledge graphs, but is incremental as it reviews existing work without presenting new results.

The paper provides an overview of neural network-based approaches for question answering over knowledge graphs, introducing challenges, current paradigms, notable advancements, and emerging trends to help newcomers enter the field.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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