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Open AccessArticle

Retrieving Landmark Salience Based on Wikipedia: An Integrated Ranking Model

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Mapping and Geo-Information Engineering, Civil and Environmental Engineering Faculty, Technion – Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
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Centre for Advanced Spatial Analysis, Bartlett Faculty of the Built Environment, University College London, London, WC1E 6BT, UK
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Mapping and Geo-Information Engineering, Civil and Environmental Engineering Faculty, Technion – Israel Institute of Technology, Technion City, Haifa, 3200003, Israel
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2019, 8(12), 529; https://doi.org/10.3390/ijgi8120529
Received: 4 September 2019 / Revised: 19 November 2019 / Accepted: 24 November 2019 / Published: 26 November 2019
(This article belongs to the Special Issue Convergence of GIS and Social Media)
Landmarks are important for assisting in wayfinding and navigation and for enriching user experience. Although many user-generated geotagged sources exist, landmark entities are still mostly retrieved from authoritative geographic sources. Wikipedia, the world’s largest free encyclopedia, stores geotagged information on many geospatial entities, including a very large and well-founded volume of landmark information. However, not all Wikipedia geotagged landmark entities can be considered valuable and instructive. This research introduces an integrated ranking model for mining landmarks from Wikipedia predicated on estimating and weighting their salience. Other than location, the model is based on the entries’ category and attributed data. Preliminary ranking is formulated on the basis of three spatial descriptors associated with landmark salience, namely permanence, visibility, and uniqueness. This ranking is integrated with a score derived from a set of numerical attributes that are associated with public interest in the Wikipedia page―including the number of redirects and the date of the latest edit. The methodology is comparatively evaluated for various areas in different cities. Results show that the developed integrated ranking model is robust in identifying landmark salience, paving the way for incorporation of Wikipedia’s content into navigation systems.
Keywords: Wikipedia; landmark salience; spatial cognition; data mining; user-generated content Wikipedia; landmark salience; spatial cognition; data mining; user-generated content
MDPI and ACS Style

Binski, N.; Natapov, A.; Dalyot, S. Retrieving Landmark Salience Based on Wikipedia: An Integrated Ranking Model. ISPRS Int. J. Geo-Inf. 2019, 8, 529.

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