Publicacions CVC -- Edit Record

	Publicacions CVC Home \| Show All \| Simple Search \| Advanced Search \| Add Record \| Import	You must login to submit this form! Login Quick Search: Field: contains: ...
	Edit the following record:

Author	...				is Editor
Title	...			Type
Year	...	Publication	...	Abbreviated Journal	...
Volume	...	Issue	...	Pages	...
Keywords	...
Abstract	The use of administrative documents to communicate and leave record of business information requires of methods able to automatically extract and understand the content from such documents in a robust and efficient way. In addition, the semi-structured nature of these reports is specially suited for the use of graph-based representations which are flexible enough to adapt to the deformations from the different document templates. Moreover, Graph Neural Networks provide the proper methodology to learn relations among the data elements in these documents. In this work we study the use of Graph Neural Network architectures to tackle the problem of entity recognition and relation extraction in semi-structured documents. Our approach achieves state of the art results in the three tasks involved in the process. Additionally, the experimentation with two datasets of different nature demonstrates the good generalization ability of our approach.
Address	...
Corporate Author	...			Thesis
Publisher	...	Place of Publication	...	Editor	...
Language	...	Summary Language	...	Original Title	...
Series Editor	...	Series Title	...	Abbreviated Series Title	...
Series Volume	...	Series Issue	...	Edition	...
ISSN	...	ISBN	...	Medium	...
Area	...	Expedition	...	Conference	...
Notes	...			Approved	yes no
Location
Call Number	...			Serial
Marked	yes no	Copy		Selected	yes no
User Keys	...
User Notes	...			User File	...
User Groups	...			Cite Key	...
Related	...
File
URL	...			DOI	...
	Online publication. Cite with this text: ...

Location Field:	my name & email address

Home

SQL Search | Library Search | Show Record | Extract Citations

Help