Ruben Verborgh’s data

Matches in Ruben’s data for { <https://ruben.verborgh.org/publications/hengchen_docsi_2015/#publication> ?p ?o }

• publication author simon_hengchen.
• publication author seth_van_hooland.
• publication author max_de_wilde.
• publication author me.
• publication creator simon_hengchen.
• publication creator seth_van_hooland.
• publication creator max_de_wilde.
• publication creator me.
• publication about Research.
• publication about Metadata.
• publication author simon_hengchen.
• publication author seth_van_hooland.
• publication author max_de_wilde.
• publication author me.
• publication coparticipatesWith simon_hengchen.
• publication coparticipatesWith seth_van_hooland.
• publication coparticipatesWith max_de_wilde.
• publication coparticipatesWith me.
• publication type PublicationIssue.
• publication type Issue.
• publication type CollectedDocument.
• publication type PublicationVolume.
• publication type ScholarlyArticle.
• publication type Article.
• publication type Document.
• publication type Document.
• publication type Document.
• publication type Q386724.
• publication type CreativeWork.
• publication type Work.
• publication P50 simon_hengchen.
• publication P50 seth_van_hooland.
• publication P50 max_de_wilde.
• publication P50 me.
• publication maker simon_hengchen.
• publication maker seth_van_hooland.
• publication maker max_de_wilde.
• publication maker me.
• publication title "L’extraction d’entités nommées : une opportunité pour le secteur culturel ?".
• publication isPartOf information_donnees_et_documents.
• publication name "L’extraction d’entités nommées : une opportunité pour le secteur culturel ?".
• publication label "L’extraction d’entités nommées : une opportunité pour le secteur culturel ?".
• publication name "L’extraction d’entités nommées : une opportunité pour le secteur culturel ?".
• publication topic Research.
• publication topic Metadata.
• publication subject Research.
• publication subject Metadata.
• publication authorList b0_b2884.
• publication topic Research.
• publication topic Metadata.
• publication abstract "Non-structured descriptive metadata provide additional benefits for end-user comprehension. However, their unstructured nature minimize their usefulness in an automated, digital context. This article explores the potential and the limits of Named Entity Recognition (NER) and Term Extraction (TE) in unstructured data searches in order to extract some meaningful concepts. These concepts allow us to benefit from improved retrieval and navigation, but they also play a very important role in digital humanities research. Using a case study to promote NER and TE experiments, based on the descriptive fields of the historical archives of Quebec City, the authors assess four third-party entity extractors. In an effort to address both NER and TE to assess named entities, they use a quantitative approach based on precision, recall and F-score calculated on the "gold standard corpus". A second more qualitative approach then leads us to consider the relevance of TE and to address the issue of multilingualism.".
• publication datePublished "2015".
• publication mainEntityOfPage hengchen_docsi_2015.
• publication sameAs publication.
• publication isPrimaryTopicOf hengchen_docsi_2015.
• publication page hengchen_docsi_2015.
• publication number "70".
• publication number "2".
• publication number "79".
• publication number "52".
• publication volume "52".
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