Geographic Information Extraction from Texts (GeoExT)

Xuke Hu; Yingjie Hu; Bernd Resch; Jens Kersten

doi:10.1007/978-3-031-28241-6_44

Geographic Information Extraction from Texts (GeoExT)

Xuke Hu
, Yingjie Hu
, Bernd Resch
, Jens Kersten

Geography

German Aerospace Center
University of Salzburg

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Scopus citations

Abstract

A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction.

Original language	English
Title of host publication	Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings
Editors	Jaap Kamps, Lorraine Goeuriot, Fabio Crestani, Maria Maistro, Hideo Joho, Brian Davis, Cathal Gurrin, Annalina Caputo, Udo Kruschwitz
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	398-404
Number of pages	7
ISBN (Print)	9783031282409
DOIs	https://doi.org/10.1007/978-3-031-28241-6_44
State	Published - 2023
Event	45th European Conference on Information Retrieval, ECIR 2023 - Dublin, Ireland Duration: Apr 2 2023 → Apr 6 2023

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	13982 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	45th European Conference on Information Retrieval, ECIR 2023
Country/Territory	Ireland
City	Dublin
Period	04/2/23 → 04/6/23

Keywords

Document geolocation
Geographic information extraction
Geoparsing
Toponym recognition
Toponym resolution

Access to Document

10.1007/978-3-031-28241-6_44

Cite this

Hu, X., Hu, Y., Resch, B., & Kersten, J. (2023). Geographic Information Extraction from Texts (GeoExT). In J. Kamps, L. Goeuriot, F. Crestani, M. Maistro, H. Joho, B. Davis, C. Gurrin, A. Caputo, & U. Kruschwitz (Eds.), Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings (pp. 398-404). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13982 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-28241-6_44

Hu, Xuke ; Hu, Yingjie ; Resch, Bernd et al. / Geographic Information Extraction from Texts (GeoExT). Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings. editor / Jaap Kamps ; Lorraine Goeuriot ; Fabio Crestani ; Maria Maistro ; Hideo Joho ; Brian Davis ; Cathal Gurrin ; Annalina Caputo ; Udo Kruschwitz. Springer Science and Business Media Deutschland GmbH, 2023. pp. 398-404 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction.",

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author = "Xuke Hu and Yingjie Hu and Bernd Resch and Jens Kersten",

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Hu, X, Hu, Y, Resch, B & Kersten, J 2023, Geographic Information Extraction from Texts (GeoExT). in J Kamps, L Goeuriot, F Crestani, M Maistro, H Joho, B Davis, C Gurrin, A Caputo & U Kruschwitz (eds), Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13982 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 398-404, 45th European Conference on Information Retrieval, ECIR 2023, Dublin, Ireland, 04/2/23. https://doi.org/10.1007/978-3-031-28241-6_44

Geographic Information Extraction from Texts (GeoExT). / Hu, Xuke; Hu, Yingjie; Resch, Bernd et al.
Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings. ed. / Jaap Kamps; Lorraine Goeuriot; Fabio Crestani; Maria Maistro; Hideo Joho; Brian Davis; Cathal Gurrin; Annalina Caputo; Udo Kruschwitz. Springer Science and Business Media Deutschland GmbH, 2023. p. 398-404 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13982 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Hu, Yingjie

AU - Resch, Bernd

AU - Kersten, Jens

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Y1 - 2023

N2 - A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction.

AB - A large volume of unstructured texts, containing valuable geographic information, is available online. This information – provided implicitly or explicitly – is useful not only for scientific studies (e.g., spatial humanities) but also for many practical applications (e.g., geographic information retrieval). Although large progress has been achieved in geographic information extraction from texts, there are still unsolved challenges and issues, ranging from methods, systems, and data, to applications and privacy. Therefore, this workshop will provide a timely opportunity to discuss the recent advances, new ideas, and concepts but also identify research gaps in geographic information extraction.

KW - Document geolocation

KW - Geographic information extraction

KW - Geoparsing

KW - Toponym recognition

KW - Toponym resolution

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DO - 10.1007/978-3-031-28241-6_44

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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A2 - Maistro, Maria

A2 - Joho, Hideo

A2 - Davis, Brian

A2 - Gurrin, Cathal

A2 - Caputo, Annalina

A2 - Kruschwitz, Udo

PB - Springer Science and Business Media Deutschland GmbH

T2 - 45th European Conference on Information Retrieval, ECIR 2023

Y2 - 2 April 2023 through 6 April 2023

ER -

Hu X, Hu Y, Resch B, Kersten J. Geographic Information Extraction from Texts (GeoExT). In Kamps J, Goeuriot L, Crestani F, Maistro M, Joho H, Davis B, Gurrin C, Caputo A, Kruschwitz U, editors, Advances in Information Retrieval - 45th European Conference on Information Retrieval, ECIR 2023, Proceedings. Springer Science and Business Media Deutschland GmbH. 2023. p. 398-404. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-28241-6_44