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

Gengchen Mai, Krzysztof Janowicz, Rui Zhu, Ling Cai, Ni Lao

Abstract: Articles | Volume 2 ArticleMetricsRelated articles Articles | Volume 2 https://doi.org/10.5194/agile-giss-2-8-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. https://doi.org/10.5194/agile-giss-2-8-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Articles | Volume 2 ArticleMetricsRelated articles 04 Jun 2021 | 04 Jun 2021 Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions Gengchen Mai, Krzysztof Janowicz, Rui Zhu, Ling Cai, and Ni Lao Gengchen Mai × STKO Lab, Department of Geography, University of California, Santa Barbara, CA, USA Center for Spatial Studies, University of California, Santa Barbara, CA, USA Krzysztof Janowicz × STKO Lab, Department of Geography, University of California, Santa Barbara, CA, USA Center for Spatial Studies, University of California, Santa Barbara, CA, USA Rui Zhu × STKO Lab, Department of Geography, University of California, Santa Barbara, CA, USA Center for Spatial Studies, University of California, Santa Barbara, CA, USA Ling Cai × STKO Lab, Department of Geography, University of California, Santa Barbara, CA, USA Center for Spatial Studies, University of California, Santa Barbara, CA, USA Ni Lao × Palo Alto, CA, USA Keywords: geographic question answering, geographic question classification, geo-semantics, knowledge graphs 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. Download & links Article (PDF, 5714 KB) Download & links Article (5714 KB) Metadata XML BibTeX EndNote Share How to cite. Mai, G., Janowicz, K., Zhu, R., Cai, L., and Lao, N.: Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions, AGILE GIScience Ser., 2, 8, https://doi.org/10.5194/agile-giss-2-8-2021, 2021.