Matches in SemOpenAlex for { <https://semopenalex.org/work/W2799687610> ?p ?o ?g. }
- W2799687610 endingPage "20" @default.
- W2799687610 startingPage "1" @default.
- W2799687610 abstract "This article describes an approach for the automated reading of biomedical data dictionaries. Automated reading is the process of extracting element details for each of the data elements from a data dictionary in a document format (such as PDF) to a completely structured representation. A structured representation is essential if the data dictionary metadata are to be used in applications such as data integration and also in evaluating the quality of the associated data. We present an approach and implemented solution for the problem, considering different formats of data dictionaries. We have a particular focus on the most challenging format with a machine-learning classification solution to the problem using conditional random field classifiers. We present an evaluation using several actual data dictionaries, demonstrating the effectiveness of our approach." @default.
- W2799687610 created "2018-05-17" @default.
- W2799687610 creator A5034548846 @default.
- W2799687610 creator A5035691684 @default.
- W2799687610 date "2017-12-31" @default.
- W2799687610 modified "2023-10-03" @default.
- W2799687610 title "Machine Reading of Biomedical Data Dictionaries" @default.
- W2799687610 cites W1511676561 @default.
- W2799687610 cites W1826790618 @default.
- W2799687610 cites W2034797903 @default.
- W2799687610 cites W2042448356 @default.
- W2799687610 cites W2093559286 @default.
- W2799687610 cites W2096496923 @default.
- W2799687610 cites W2102189859 @default.
- W2799687610 cites W2109140840 @default.
- W2799687610 cites W2131240202 @default.
- W2799687610 cites W2133990480 @default.
- W2799687610 cites W2136500370 @default.
- W2799687610 cites W2143309843 @default.
- W2799687610 cites W2148317291 @default.
- W2799687610 cites W2294792814 @default.
- W2799687610 doi "https://doi.org/10.1145/3177874" @default.
- W2799687610 hasPublicationYear "2017" @default.
- W2799687610 type Work @default.
- W2799687610 sameAs 2799687610 @default.
- W2799687610 citedByCount "0" @default.
- W2799687610 crossrefType "journal-article" @default.
- W2799687610 hasAuthorship W2799687610A5034548846 @default.
- W2799687610 hasAuthorship W2799687610A5035691684 @default.
- W2799687610 hasConcept C116409475 @default.
- W2799687610 hasConcept C120665830 @default.
- W2799687610 hasConcept C121332964 @default.
- W2799687610 hasConcept C124101348 @default.
- W2799687610 hasConcept C136764020 @default.
- W2799687610 hasConcept C152565575 @default.
- W2799687610 hasConcept C154945302 @default.
- W2799687610 hasConcept C162324750 @default.
- W2799687610 hasConcept C176217482 @default.
- W2799687610 hasConcept C17744445 @default.
- W2799687610 hasConcept C192209626 @default.
- W2799687610 hasConcept C199360897 @default.
- W2799687610 hasConcept C199539241 @default.
- W2799687610 hasConcept C202444582 @default.
- W2799687610 hasConcept C204321447 @default.
- W2799687610 hasConcept C21547014 @default.
- W2799687610 hasConcept C23123220 @default.
- W2799687610 hasConcept C24756922 @default.
- W2799687610 hasConcept C2776359362 @default.
- W2799687610 hasConcept C30872290 @default.
- W2799687610 hasConcept C33923547 @default.
- W2799687610 hasConcept C41008148 @default.
- W2799687610 hasConcept C554936623 @default.
- W2799687610 hasConcept C93518851 @default.
- W2799687610 hasConcept C94625758 @default.
- W2799687610 hasConcept C9652623 @default.
- W2799687610 hasConcept C98045186 @default.
- W2799687610 hasConcept C98143201 @default.
- W2799687610 hasConceptScore W2799687610C116409475 @default.
- W2799687610 hasConceptScore W2799687610C120665830 @default.
- W2799687610 hasConceptScore W2799687610C121332964 @default.
- W2799687610 hasConceptScore W2799687610C124101348 @default.
- W2799687610 hasConceptScore W2799687610C136764020 @default.
- W2799687610 hasConceptScore W2799687610C152565575 @default.
- W2799687610 hasConceptScore W2799687610C154945302 @default.
- W2799687610 hasConceptScore W2799687610C162324750 @default.
- W2799687610 hasConceptScore W2799687610C176217482 @default.
- W2799687610 hasConceptScore W2799687610C17744445 @default.
- W2799687610 hasConceptScore W2799687610C192209626 @default.
- W2799687610 hasConceptScore W2799687610C199360897 @default.
- W2799687610 hasConceptScore W2799687610C199539241 @default.
- W2799687610 hasConceptScore W2799687610C202444582 @default.
- W2799687610 hasConceptScore W2799687610C204321447 @default.
- W2799687610 hasConceptScore W2799687610C21547014 @default.
- W2799687610 hasConceptScore W2799687610C23123220 @default.
- W2799687610 hasConceptScore W2799687610C24756922 @default.
- W2799687610 hasConceptScore W2799687610C2776359362 @default.
- W2799687610 hasConceptScore W2799687610C30872290 @default.
- W2799687610 hasConceptScore W2799687610C33923547 @default.
- W2799687610 hasConceptScore W2799687610C41008148 @default.
- W2799687610 hasConceptScore W2799687610C554936623 @default.
- W2799687610 hasConceptScore W2799687610C93518851 @default.
- W2799687610 hasConceptScore W2799687610C94625758 @default.
- W2799687610 hasConceptScore W2799687610C9652623 @default.
- W2799687610 hasConceptScore W2799687610C98045186 @default.
- W2799687610 hasConceptScore W2799687610C98143201 @default.
- W2799687610 hasFunder F4320306219 @default.
- W2799687610 hasIssue "4" @default.
- W2799687610 hasLocation W27996876101 @default.
- W2799687610 hasOpenAccess W2799687610 @default.
- W2799687610 hasPrimaryLocation W27996876101 @default.
- W2799687610 hasRelatedWork W163038166 @default.
- W2799687610 hasRelatedWork W2151972543 @default.
- W2799687610 hasRelatedWork W2361349944 @default.
- W2799687610 hasRelatedWork W2383201407 @default.
- W2799687610 hasRelatedWork W2506176693 @default.
- W2799687610 hasRelatedWork W2946081857 @default.
- W2799687610 hasRelatedWork W4236158639 @default.
- W2799687610 hasRelatedWork W4239980582 @default.