Semantic Scholar Open Access 2021 71 sitasi

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

Gengchen Mai K. Janowicz Rui Zhu Ling Cai N. Lao

Abstrak

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.

Topik & Kata Kunci

Penulis (5)

G

Gengchen Mai

K

K. Janowicz

R

Rui Zhu

L

Ling Cai

N

N. Lao

Format Sitasi

Mai, G., Janowicz, K., Zhu, R., Cai, L., Lao, N. (2021). Geographic Question Answering: Challenges, Uniqueness, Classification, and Future Directions. https://doi.org/10.5194/AGILE-GISS-2-8-2021

Akses Cepat

Lihat di Sumber doi.org/10.5194/AGILE-GISS-2-8-2021
Informasi Jurnal
Tahun Terbit
2021
Bahasa
en
Total Sitasi
71×
Sumber Database
Semantic Scholar
DOI
10.5194/AGILE-GISS-2-8-2021
Akses
Open Access ✓