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Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions

2021-05-19 20:47:36
Gengchen Mai, Krzysztof Janowicz, Rui Zhu, Ling Cai, Ni Lao
arXiv_AI
         
Abstract

As an important part of Artificial Intelligence (AI), Question Answering (QA) aims at generating answers to questions phrased in natural language. While there has been substantial progress in open-domain question answering, QA systems are still struggling to answer questions which involve geographic entities or concepts and that require spatial operations. In this paper, we discuss the problem of geographic question answering (GeoQA). We first investigate the reasons why geographic questions are difficult to answer by analyzing challenges of geographic questions. We discuss the uniqueness of geographic questions compared to general QA. Then we review existing work on GeoQA and classify them by the types of questions they can address. Based on this survey, we provide a generic classification framework for geographic questions. Finally, we conclude our work by pointing out unique future research directions for GeoQA.

Abstract (translated)

URL

https://arxiv.org/abs/2105.09392

PDF

https://arxiv.org/pdf/2105.09392.pdf

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