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Search Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking

Ferrari, Elia ; Striewski, Friedrich ; Tiefenbacher, Fiona ; Bereuter, Pia ; Oesch, David ; Di Donato, Pasquale

ISPRS international journal of geo-information, 2024-04, Vol.13 (4), p.128 [Periódico revisado por pares]

Basel: MDPI AG

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Título:
Search Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking
Autor: Ferrari, Elia ; Striewski, Friedrich ; Tiefenbacher, Fiona ; Bereuter, Pia ; Oesch, David ; Di Donato, Pasquale
Assuntos: Computational linguistics ; Consortia ; data discovery ; Data retrieval ; Datasets ; Engines ; Feasibility studies ; Geospatial data ; geospatial search engine ; Information retrieval ; Information services ; Information storage and retrieval ; Internet ; Internet service providers ; Internet/Web search services ; Language ; Language processing ; Metadata ; Natural language interfaces ; Natural Language Processing ; Online information services ; Online services ; Ontology ; Open Geospatial Consortium ; Queries ; Ranking ; Rankings ; result ranking ; Search engines ; Semantic web ; Semantics ; Spatial data ; Web services ; World Wide Web
É parte de: ISPRS international journal of geo-information, 2024-04, Vol.13 (4), p.128
Descrição: The improvement of search engines for geospatial data on the World Wide Web has been a subject of research, particularly concerning the challenges in discovering and utilizing geospatial web services. Despite the establishment of standards by the Open Geospatial Consortium (OGC), the implementation of these services varies significantly among providers, leading to issues in dataset discoverability and usability. This paper presents a proof of concept for a search engine tailored to geospatial services in Switzerland. It addresses challenges such as scraping data from various OGC web service providers, enhancing metadata quality through Natural Language Processing, and optimizing search functionality and ranking methods. Semantic augmentation techniques are applied to enhance metadata completeness and quality, which are stored in a high-performance NoSQL database for efficient data retrieval. The results show improvements in dataset discoverability and search relevance, with NLP-extracted information contributing significantly to ranking accuracy. Overall, the GeoHarvester proof of concept demonstrates the feasibility of improving the discoverability and usability of geospatial web services through advanced search engine techniques.
Editor: Basel: MDPI AG
Idioma: Inglês

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Search Engine for Open Geospatial Consortium Web Services Improving Discoverability through Natural Language Processing-Based Processing and Ranking

Ferrari, Elia ; Striewski, Friedrich ; Tiefenbacher, Fiona ; Bereuter, Pia ; Oesch, David ; Di Donato, Pasquale

Basel: MDPI AG

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