Photographing a City: An Analysis of Place Concepts Based on Spatial Choices

Abstract We ask whether the photographs published in web-based image collections do represent different conceptualizations of a city and present a method for gathering and analyzing a data set of more than 12,000 images from Amsterdam, Bamberg, Cardiff, and Dublin. We then propose a measure for the popularity of a location in a city. The analysis of the data set reveals that the popularity follows a power law with very few highly popular locations and a long tail of places in a city that are visited only occasionally. The most popular locations can be identified with the semantic core of the conceptualization of the city in terms of images. This raises the issue of individual differences. We propose another measure that permits to identify users with similar conceptualizations of a city.

[1]  John Riedl,et al.  GroupLens: an open architecture for collaborative filtering of netnews , 1994, CSCW '94.

[2]  Angela Schwering,et al.  Approaches to Semantic Similarity Measurement for Geo‐Spatial Data: A Survey , 2008, Trans. GIS.

[3]  M. Bishr,et al.  Geospatial Information Bottom-Up: A Matter of Trust and Semantics , 2007, AGILE Conf..

[4]  A. Tversky Features of Similarity , 1977 .

[5]  W. A. Labuschagne Review: Peter Gärdenfors, Conceptual Spaces: "The Geometry of Thought" (Cambridge Mass.: MIT, 2000) , 2005 .

[6]  Thomas Gruber,et al.  Ontology of Folksonomy: A Mash-Up of Apples and Oranges , 2007, Int. J. Semantic Web Inf. Syst..

[7]  E. Rosch ON THE INTERNAL STRUCTURE OF PERCEPTUAL AND SEMANTIC CATEGORIES1 , 1973 .

[8]  Max J. Egenhofer,et al.  Comparing geospatial entity classes: an asymmetric and context-dependent similarity measure , 2004, Int. J. Geogr. Inf. Sci..

[9]  Mor Naaman,et al.  Methods for extracting place semantics from Flickr tags , 2009, TWEB.

[10]  Christoph Schlieder,et al.  Modeling Collaborative Semantics with a Geographic Recommender , 2007, ER Workshops.

[11]  Xing Xie,et al.  Mining interesting locations and travel sequences from GPS trajectories , 2009, WWW '09.

[12]  Marieke Guy,et al.  Folksonomies: Tidying Up Tags? , 2006, D Lib Mag..

[13]  Angela Schwering,et al.  Semantic Similarity Measurement and Geospatial Applications , 2008, Trans. GIS.

[14]  Philip Resnik,et al.  Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language , 1999, J. Artif. Intell. Res..

[15]  Steven M. Seitz,et al.  Photo tourism: exploring photo collections in 3D , 2006, ACM Trans. Graph..

[16]  Thad Starner,et al.  Learning Significant Locations and Predicting User Movement with GPS , 2002, Proceedings. Sixth International Symposium on Wearable Computers,.

[17]  Robin D. Burke,et al.  Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.

[18]  Nitya Narasimhan,et al.  Using location for personalized POI recommendations in mobile environments , 2006, International Symposium on Applications and the Internet (SAINT'06).

[19]  Josep Blat,et al.  Leveraging explicitly disclosed location information to understand tourist dynamics: a case study , 2008, J. Locat. Based Serv..

[20]  F. Girardin,et al.  Understanding of Tourist Dynamics from Explicitly Disclosed Location Information , 2007 .

[21]  Michael R. Curry,et al.  Discursive Displacement and the Seminal Ambiguity of Space and Place , 2002 .

[22]  A. Morris,et al.  Digital trail libraries , 2004, Proceedings of the 2004 Joint ACM/IEEE Conference on Digital Libraries, 2004..

[23]  GeunSik Jo,et al.  Location-Based Service with Context Data for a Restaurant Recommendation , 2006, DEXA.