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

2019/07/22 by Nilesh Chakraborty, Chakraborty, Nilesh, Denis Lukovnikov +9
Computer Science · #Advanced Graph Neural Networks #Artificial Intelligence (cs.AI) #Computation and Language (cs.CL) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Natural Language Processing Techniques #Topic Modeling #cs.AI #cs.CL #cs.LG

paper · pdf · doi:10.48550/arxiv.1907.09361

Preprint, under review. The first four authors contributed equally to this paper, and should be regarded as co-first authors

arxiv created 2019/07/22 · openalex publication_date 2019/07/22 · arxiv updated 2019/07/23 · openalex created_date 2019/07/30 · openalex updated_date 2026/07/28

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.

Citations

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Related

• Strong Baselines for Simple Question Answering over Knowledge Graphs with and without Neural Networks
• A Heterogeneous Graph with Factual, Temporal and Logical Knowledge for Question Answering Over Dynamic Contexts
• Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Information
• Learning to Rank Query Graphs for Complex Question Answering over Knowledge Graphs
• Open Domain Question Answering Using Early Fusion of Knowledge Bases and Text