The Information Retrieval research has used semantics to provide accurate search results, but the analysis of conceptual abstraction has mainly focused on information integration. We consider session-based query expansion in Geographical Information Retrieval, and investigate the impact of semantic granularity (i.e., specificity of concepts representation) on the suggestion of relevant types of information to search for. We study how different levels of detail in knowledge representation influence the capability of guiding the user in the exploration of a complex information space. A comparative analysis of the performance of a query expansion model, using three spatial ontologies defined at different semantic granularity levels, reveals that a fine-grained representation enhances recall. However, precision depends on how closely the ontologies match the way people conceptualize and verbally describe the geographic space.

Impact of Semantic Granularity on Geographic Information Search Support

N. Mauro;L. Ardissono;
2019-01-01

Abstract

The Information Retrieval research has used semantics to provide accurate search results, but the analysis of conceptual abstraction has mainly focused on information integration. We consider session-based query expansion in Geographical Information Retrieval, and investigate the impact of semantic granularity (i.e., specificity of concepts representation) on the suggestion of relevant types of information to search for. We study how different levels of detail in knowledge representation influence the capability of guiding the user in the exploration of a complex information space. A comparative analysis of the performance of a query expansion model, using three spatial ontologies defined at different semantic granularity levels, reveals that a fine-grained representation enhances recall. However, precision depends on how closely the ontologies match the way people conceptualize and verbally describe the geographic space.
2019
2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)
Santiago de Chile
03-06/12/2018
2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)
IEEE Press
323
328
978-1-5386-7325-6
https://ieeexplore.ieee.org/document/8609610
geographical information retrieval, semantic granularity, session-based concept suggestion
N. Mauro, L. Ardissono, L. Di Rocco, G. Guerrini, M. Bertolotto
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/1684430
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