Universität Wien

290705 VU Geographic Information Retrieval (2025W)

5.00 ECTS (2.00 SWS), SPL 29 - Geographie
Prüfungsimmanente Lehrveranstaltung
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 30 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Donnerstag 09.10. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 16.10. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 23.10. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 30.10. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 13.11. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 20.11. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 27.11. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 11.12. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 18.12. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 15.01. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG
  • Donnerstag 22.01. 12:30 - 14:30 GIS-Labor Geo NIG 1.OG

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

The size, modality, and source of information about places and regions across the world are constantly changing. To support downstream tasks like question answering, geographic information retrieval (GIR) provides us with an approach of accessing, searching, indexing, and integrating geographic information. Applications related to GIR include the construction of gazetteers, Web search, and location-based recommendation.

The course will cover GIR’s core concepts, techniques and challenges, such as place name ambiguity, georeferencing, indexing and ranking, and natural language processing. Through literature review and Python-based practical exercises, students will learn how to query structured data from geographic databases, how to geoparse and geocode unstructured texts, and how to achieve semantic analysis with retrieved information.

Course content from the past year is available at: https://meilinshi.github.io/290061-Geographic-Information-Retrieval/intro.html

Art der Leistungskontrolle und erlaubte Hilfsmittel

Participation (10%)
4 quizzes (40%)
1 midterm exam (20%)
1 final exam (30%)

Mindestanforderungen und Beurteilungsmaßstab

Personal contribution that demonstrates an appropriate understanding of the approaches and methods discussed.

100 % - 88 % = 1
87 % - 75 % = 2
74 % - 63 % = 3
62 % - 51 % = 4
Below 51 % = 5

Prüfungsstoff

Core concepts, techniques, challenges, and programming skills in geographic information retrieval

Literatur

1. Purves, R. S., Clough, P., Jones, C. B., Hall, M. H., & Murdock, V. (2018). Geographic information retrieval: Progress and challenges in spatial search of text. Foundations and Trends® in Information Retrieval, 12(2-3), 164-318.
2. Presentation and slides (including references)

Zuordnung im Vorlesungsverzeichnis

(MSDS-S) (MSDS-IS) (MK1-W1) (MK2)

Letzte Änderung: Di 07.10.2025 10:27