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User-Centric Similarity and Proximity Measures for Spatial Personalization

User-Centric Similarity and Proximity Measures for Spatial Personalization

Yanwu Yang, Christophe Claramunt, Marie-Aude Aufaure, Wensheng Zhang
Copyright: © 2010 |Volume: 6 |Issue: 2 |Pages: 20
ISSN: 1548-3924|EISSN: 1548-3932|EISBN13: 9781609603878|DOI: 10.4018/jdwm.2010040104
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MLA

Yang, Yanwu, et al. "User-Centric Similarity and Proximity Measures for Spatial Personalization." IJDWM vol.6, no.2 2010: pp.59-78. http://doi.org/10.4018/jdwm.2010040104

APA

Yang, Y., Claramunt, C., Aufaure, M., & Zhang, W. (2010). User-Centric Similarity and Proximity Measures for Spatial Personalization. International Journal of Data Warehousing and Mining (IJDWM), 6(2), 59-78. http://doi.org/10.4018/jdwm.2010040104

Chicago

Yang, Yanwu, et al. "User-Centric Similarity and Proximity Measures for Spatial Personalization," International Journal of Data Warehousing and Mining (IJDWM) 6, no.2: 59-78. http://doi.org/10.4018/jdwm.2010040104

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Abstract

Spatial personalization can be defined as a novel way to fulfill user information needs when accessing spatial information services either on the web or in mobile environments. The research presented in this paper introduces a conceptual approach that models the spatial information offered to a given user into a user-centered conceptual map, and spatial proximity and similarity measures that considers her/his location, interests and preferences. This approach is based on the concepts of similarity in the semantic domain, and proximity in the spatial domain, but taking into account user’s personal information. Accordingly, these spatial proximity and similarity measures could directly support derivation of personalization services and refinement of the way spatial information is accessible to the user in spatially related applications. These modeling approaches are illustrated by some experimental case studies.

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