LexFCS – Extending the Federated Content Search for Lexical Resources

The CLARIN Federated Content Search (FCS) is a search engine that connects local data collections. It allows researchers to search for specific patterns in collections from distributed data centres. We demonstrate the new, planned LexFCS extension to enable the search and visualization of results from lexical resources that have a different inherent structure, which poses new challenges but their integration will ultimately enrich the FCS resource ecosystem. Insights into the work of the German project Text+ show our current efforts to integrate lexical resources into the FCS using custom Data Formats, Query Languages and UI integrations to enable search through dictionaries, wordnets and similar.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-10-16
DOI
https://doi.org/10.5281/zenodo.14012996
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
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article

LexFCS – Extending the Federated Content Search for Lexical Resources

Zenodo (CERN European Organization for Nuclear Research)
Biomedical Text Mining and Ontologies
article

LexFCS – Extending the Federated Content Search for Lexical Resources

article en

Abstract

The CLARIN Federated Content Search (FCS) is a search engine that connects local data collections. It allows researchers to search for specific patterns in collections from distributed data centres. We demonstrate the new, planned LexFCS extension to enable the search and visualization of results from lexical resources that have a different inherent structure, which poses new challenges but their integration will ultimately enrich the FCS resource ecosystem. Insights into the work of the German project Text+ show our current efforts to integrate lexical resources into the FCS using custom Data Formats, Query Languages and UI integrations to enable search through dictionaries, wordnets and similar.

Zenodo (CERN European Organization for Nuclear Research)
Saxon Academy of Sciences and Humanities in Leipzig (DE)
Quality Education
Openalex Percentile: Top 64%
Biomedical Text Mining and Ontologies
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