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Classifiers

Property	Description
Short description	A document classification algorithm that employs analysis of free text stemming from the abstracts of the publications. The purpose of applying a document classification module is to assign a scientific text to one or more predefined content classes.
Authority	ATHENA Research Center, Greece
Licence	CC-BY/CC-0
Algorithmic details	The algorithm classifies publication's fulltexts using a Bayesian classifier and weighted terms according to an offline training phase. The training has been done using the following taxonomies: arXiv, MeSH (Medical Subject Headings), ACM, and DDC (Dewey Decimal Classification, or Dewey Decimal System).
Parameters	Publication's identifier and fulltext
Limitations	N/A
Code repository	https://github.com/openaire/iis/tree/master/iis-wf/iis-wf-referenceextraction/src/main/resources/eu/dnetlib/iis/wf/referenceextraction
Environment	Python, madIS (https://github.com/madgik/madis), APSW (https://github.com/rogerbinns/apsw)
References & resources	Giannakopoulos, T., Stamatogiannakis, E., Foufoulas, I., Dimitropoulos, H., Manola, N., Ioannidis, Y. (2014). Content Visualization of Scientific Corpora Using an Extensible Relational Database Implementation. In: Bolikowski, Ł., Casarosa, V., Goodale, P., Houssos, N., Manghi, P., Schirrwagen, J. (eds) Theory and Practice of Digital Libraries -- TPDL 2013 Selected Workshops. TPDL 2013. Communications in Computer and Information Science, vol 416. Springer, Cham.