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A knowledge infrastructure for intelligent query answering in location-based services

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Abstract

Intelligent query answering in Location-based Services refers to their capability to provide mobile users with personalized and contextualized answers. Personalization is expected to lead to answers that better match user’s interests, as inferable from the user’s profile. Contextualization aims at not selecting answers that for some reason would not be appropriate at the time and place of the user query. These goals are beyond the current state of art in LBS, or are provided based on ad hoc solutions specific to the application at hand. This paper reports on the results of an investigation aiming at defining the knowledge infrastructure that should be developed within the LBS to make it capable of returning intelligent answers. We first discuss the data management features that make LBS different from other query answering systems. Next we propose a data infrastructure that builds on the idea of modular ontologies. We explain how the relevant knowledge may be incrementally set up and dynamically maintained based on an application-independent approach. Last we show how this knowledge is used to reformulate user’s queries via personalized and contextualized rewriting.

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Notes

  1. http://www.ist-daidalos.org/ and http://www.ist-daidalos.org/

  2. See, for example, http://www.daml.org/ontologies/keyword.html

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Correspondence to Shijun Yu.

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This paper is an extended version of the paper originally presented at the Second International Workshop on Semantic and Conceptual Issues in Geographic Information Systems (SeCoGIS 2008), held in conjunction with the ER 2008 Conference, Proceedings published in LNCS 5232, Advances in Conceptual Modeling—Challenges and Opportunities, Il-Yeol Song et al. (eds), 2008. Springer, pp 364–374.

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Yu, S., Spaccapietra, S. A knowledge infrastructure for intelligent query answering in location-based services. Geoinformatica 14, 379–404 (2010). https://doi.org/10.1007/s10707-010-0105-4

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