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HESDK: A Hybrid Approach to Extracting Scientific Domain Knowledge Entities

Jian Wu, Sagnik Ray Choudhury, Agnese Chiatti, Chen Liang, C. Lee Giles
2017 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL)  
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]

Md Reshad Ul Hoque, Jiang Li, Jian Wu
2022 arXiv   pre-print
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