research-article

Joint Spatio-Textual Reasoning for Answering Tourism Questions

Authors:

Danish Contractor,

Parag SinglaAuthors Info & Claims

WWW '21: Proceedings of the Web Conference 2021

Pages 1978 - 1989

https://doi.org/10.1145/3442381.3449857

Published: 03 June 2021 Publication History

Abstract

Our goal is to answer real-world tourism questions that seek Points-of-Interest (POI) recommendations. Such questions express various kinds of spatial and non-spatial constraints, necessitating a combination of textual and spatial reasoning. In response, we develop the first joint spatio-textual reasoning model, which combines geo-spatial knowledge with information in textual corpora to answer questions. We first develop a modular spatial-reasoning network that uses geo-coordinates of location names mentioned in a question, and of candidate answer POIs, to reason over only spatial constraints. We then combine our spatial-reasoner with a textual reasoner in a joint model and present experiments on a real world POI recommendation task. We report substantial improvements over existing models without joint spatio-textual reasoning. To the best of our knowledge, we are the first to develop a joint QA model that combines reasoning over external geo-spatial knowledge along with textual reasoning.

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cover image ACM Conferences

WWW '21: Proceedings of the Web Conference 2021

April 2021

4054 pages

ISBN:9781450383127

DOI:10.1145/3442381

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Jure Leskovec
Stanford
,
Marko Grobelnik
Jožef Stefan Institute
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Google
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Jie Tang
Tsinghua University
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Leila Zia
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Published: 03 June 2021

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April 19 - 23, 2021

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Cited By

Mai GHuang WSun JSong SMishra DLiu NGao SLiu TCong GHu YCundy CLi ZZhu RLao N(2024)On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper)ACM Transactions on Spatial Algorithms and Systems10.1145/365307010:2(1-46)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1145/3653070
Qi JLuan ZHuang SFung CYang H(2024)LogSay: An Efficient Comprehension System for Log Numerical ReasoningIEEE Transactions on Computers10.1109/TC.2024.338606873:7(1809-1821)Online publication date: Jul-2024
https://doi.org/10.1109/TC.2024.3386068
Szczepanek R(2023)A Deep Learning Model of Spatial Distance and Named Entity Recognition (SD-NER) for Flood Mark Text ClassificationWater10.3390/w1506119715:6(1197)Online publication date: 20-Mar-2023
https://doi.org/10.3390/w15061197
Deng ZWeng DWu Y(2022)You are experienced: interactive tour planning with crowdsourcing tour data from webJournal of Visualization10.1007/s12650-022-00884-126:2(385-401)Online publication date: 26-Oct-2022
https://dl.acm.org/doi/10.1007/s12650-022-00884-1

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