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HESDK: A Hybrid Approach to Extracting Scientific Domain Knowledge Entities
2017
2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL)
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We investigate a variant of the problem of automatic keyphrase extraction from scienti c documents which we de ne as Scienti c Domain Knowledge Entity (SDKE) extraction. ...
A SDKE represents domain knowledge, but is not necessarily important to the document it is in. ...
As such, we de ne a new type of textual entity (phrase) for scienti c documents which we name Scienti c Domain Knowledge Entity. An SDKE represents domain knowledge. ...
doi:10.1109/jcdl.2017.7991580
dblp:conf/jcdl/WuCCLG17
fatcat:jo66is7upzfntaut7fj423642y
SciEv: Finding Scientific Evidence Papers for Scientific News
[article]
2022
arXiv
pre-print
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
The key feature of SciEv is it uses domain knowledge entities (DKEs) to find candidates in the first stage, which proved to be more effective than regular keyphrases. ...
To our best knowledge, this is the first dataset of this kind. Our experiments indicate that the transformer model performs the best for DKE extraction. ...
HESDK HESDK is a hybrid approach to extract DKEs Wu et al. [2017] . ...
arXiv:2205.00126v1
fatcat:bouw4n5xxvdftoyko5nd3dvsga