An architecture and design approach for a geographical information retrieval system to support retrieval by content and browsing★

Agosti, Maristella; Crivellari, Franco; Deambrosis, Graziano; Gradenigo, G.

doi:10.1016/0198-9715(93)90029-5

Cited by 2 publications

(2 citation statements)

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“…The previous emphasis upon coordinates is fully justified by the need to retrieve, analyse and display graphically the wealth of map-based and primary-surveyed data that are referenced to geographical and map grid coordinates. However, as more information becomes available both to environmental and social scientists and to non-specialists, the need arises to provide more intelligent information retrieval facilities that can recognise natural language concepts of space and time (Agosti et al 1993). It is also the case that much geographically-referenced information is identified by place names and other non-spatial classification terms that are not directly accessible by coordinate-based indexing methods.…”

Section: Introductionmentioning

confidence: 99%

Geographical Information Retrieval with Ontologies of Place

Jones

Alani

Tudhope

2001

Spatial Information Theory

125

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Section: Introductionmentioning

confidence: 99%

Geographical Information Retrieval with Ontologies of Place

Jones

Alani

Tudhope

2001

Spatial Information Theory

125

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“…Furthermore, GIS must be able to provide access points for geographical information collection to the final users (non-expert user of the application). In order to establish this author of (Agosti et al, 1993) introduced architecture and design approach for Geographical Information Retrieval System, which is capable of supporting the retrieval by content and browsing on textual data. It provided the framework for managing the geographical systems.…”

Section: Related Workmentioning

confidence: 99%

Efficacious Geospatial Information Retrieval Using Density Probabilistic Document Correlation Approach

Uma¹,

Muneeswaran²

2013

Journal of Computer Science

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Information Retrieval (IR) is a profound technique to find information that addresses the need of query. Processing of normal text is easier and information can be retrieved efficiently. There are plenty of algorithms in hand to carry out the normal text retrieval. Whereas retrieving geospatial information is very complex and requires additional operations to be performed. Since geospatial data contain complex details than general data such as location, direction. To handle geographical queries, we proposed a Density Probabilistic Document Correlation (DPDC) approach. This approach, initially categorize the geographical features from text that satisfies the given queries. Existing text classification techniques are unsuitable for geospatial text classification due to the exclusivity of the geographical features. Depending on the DPDC approach result we predict overlap of the feature set for a document. Based on overlap and document correlation, the documents are ranked. Highly relevant documents are extracted depending on the score obtained through ranking. Documents with high score are considered the most relevant. The experimental results show that our proposed method efficiently retrieves the list of relevant documents.

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An architecture and design approach for a geographical information retrieval system to support retrieval by content and browsing★

Cited by 2 publications

References 6 publications

Geographical Information Retrieval with Ontologies of Place

Geographical Information Retrieval with Ontologies of Place

Efficacious Geospatial Information Retrieval Using Density Probabilistic Document Correlation Approach

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