Approximate spatial reasoning: integrating qualitative and quantitative constraints
International Journal of Approximate Reasoning
Imprecise reasoning in geographic information systems
Fuzzy Sets and Systems - Special issue on Uncertainty in geographic information systems and spatial data
Individual and multipersonal fuzzy spatial relations acquired using human-machine interaction
Fuzzy Sets and Systems - Special issue on Uncertainty in geographic information systems and spatial data
Wrapper induction: efficiency and expressiveness
Artificial Intelligence - Special issue on Intelligent internet systems
Computational Structure in Three-Valued Nearness Relations
COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
Comparing rankings of search results on the web
Information Processing and Management: an International Journal - Special issue: Infometrics
Automatic acquisition of fuzzy footprints
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems
Delineating boundaries for imprecise regions
ESA'05 Proceedings of the 13th annual European conference on Algorithms
Landmark extraction: a web mining approach
COSIT'05 Proceedings of the 2005 international conference on Spatial Information Theory
Fuzzy region connection calculus: An interpretation based on closeness
International Journal of Approximate Reasoning
Quantifying spatial prepositions: an experimental study
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Geographical classification of documents using evidence from Wikipedia
Proceedings of the 6th Workshop on Geographic Information Retrieval
Rewriting queries for web searches that use local expressions
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
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Local search services allow a user to search for businesses that satisfy a given geographical constraint. In contrast to traditional web search engines, current local search services rely heavily on static, structured data. Although this yields very accurate systems, it also implies a limited coverage, and limited support for using landmarks and neighborhood names in queries. To overcome these limitations, we propose to augment the structured information available to a local search service, based on the vast amount of unstructured and semi-structured data available on the web. This requires a computational framework to represent vague natural language information about the nearness of places, as well as the spatial extent of vague neighborhoods. In this paper, we propose such a framework based on fuzzy set theory, and show how natural language information can be translated into this framework. We provide experimental results that show the effectiveness of the proposed techniques, and demonstrate that local search based on natural language hints about the location of places with an unknown address, is feasible.