A linked data-based framework for personalized services information retrieval in smart city

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Abstract

Recently, personalized services finding in Smart City or Digit City is a hotspot in research area. City and urban areas contain plenty of services but some of them are difficult to extract and retrieval to people. Furthermore, with the development of the Semantic Web, more and more datasets are represented as RDF format and become part of the Linked Data, which provides a fundamentally new venue for personalized urban services retrieval in smart city applications. In this paper, we propose a personalized urban services retrieval framework which is performed by using ontology and comparing RDF-based user profiles with dataset in relation to civic services on web of data. To extract hidden information, the domain specific ontology is involved for linking entities on the web of data. The cases we envisage will show that the proposed framework can effectively return services resources with respect to the user’s interests.

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Zhang, D., Song, T., Li, J., & Liu, Q. (2014). A linked data-based framework for personalized services information retrieval in smart city. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8182, pp. 461–473). Springer Verlag. https://doi.org/10.1007/978-3-642-54370-8_39

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