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Identifying Landmark Candidates Beyond Toy Examples: A Critical Discussion and Some Way Forward
Umeå University, Faculty of Science and Technology, Department of Computing Science.ORCID iD: 0000-0001-5629-0981
2017 (English)In: Künstliche Intelligenz, ISSN 0933-1875, E-ISSN 1610-1987, Vol. 31, no 2, p. 135-139Article in journal (Refereed) Published
Abstract [en]

Incorporating references to landmarks in navigation systems requires having data on potential landmarks in the first place. While there have been many approaches in the scientific literature for identifying landmark candidates, these have hardly been picked up in actual, running systems. One major obstacle for this to happen may be that most—if not all—approaches presented so far are not scalable due to their underlying data requirements. In this paper, I will critically discuss existing approaches in light of their scalability. I will then suggest a way forward to more scalable solutions by combining in a smart way aspects of different approaches.

Place, publisher, year, edition, pages
2017. Vol. 31, no 2, p. 135-139
Keywords [en]
landmark identification, personalization, human-computer interaction, user-generated content
National Category
Human Computer Interaction
Research subject
computer and systems sciences
Identifiers
URN: urn:nbn:se:umu:diva-137162DOI: 10.1007/s13218-016-0477-1ISI: 000406351500004Scopus ID: 2-s2.0-85031296475OAI: oai:DiVA.org:umu-137162DiVA, id: diva2:1127556
Available from: 2017-07-17 Created: 2017-07-17 Last updated: 2023-03-23Bibliographically approved

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fulltext(702 kB)244 downloads
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Richter, Kai-Florian

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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf