Neighborhood Restrictions in Geographic IR. Schockaert, S. & De Cock, M. In pages 167-174.
doi  abstract   bibtex   
Geographic information retrieval (GIR) systems allow users to specify a geographic context, in addition to a more traditional query, enabling the system to pinpoint interesting search results whose relevancy is location-dependent. In particular local search services have become a widely used mechanism to find businesses, such as hotels, restaurants, and shops, which satisfy a geographical restriction. Unfortunately, many useful types of geographic restrictions are currently not supported in these systems, including restrictions that specify the neighborhood in which the business should be located. As the boundaries of city neighborhoods are not readily available, automated techniques to construct representations of the spatial extent of neighborhoods are required to support this kind of restrictions. In this paper, we propose such a technique, using fuzzy footprints to cope with the inherent vagueness of most neighborhood boundaries, and we provide experimental results that demonstrate the potential of our technique in a local search setting.
@inproceedings{ sch07d,
  crossref = {sigir07},
  author = {Steven Schockaert and Martine {De Cock}},
  title = {Neighborhood Restrictions in Geographic IR},
  pages = {167-174},
  doi = {http://doi.acm.org/10.1145/1277741.1277772},
  uri = {http://www.cwi.ugent.be/martine/papers/volledig/sschockaert2007b.pdf},
  abstract = {Geographic information retrieval (GIR) systems allow users to specify a geographic context, in addition to a more traditional query, enabling the system to pinpoint interesting search results whose relevancy is location-dependent. In particular local search services have become a widely used mechanism to find businesses, such as hotels, restaurants, and shops, which satisfy a geographical restriction. Unfortunately, many useful types of geographic restrictions are currently not supported in these systems, including restrictions that specify the neighborhood in which the business should be located. As the boundaries of city neighborhoods are not readily available, automated techniques to construct representations of the spatial extent of neighborhoods are required to support this kind of restrictions. In this paper, we propose such a technique, using fuzzy footprints to cope with the inherent vagueness of most neighborhood boundaries, and we provide experimental results that demonstrate the potential of our technique in a local search setting.}
}

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