New Similarity Function for Scientific Articles Clustering Based on the Bibliographic References

Authors

  • Lisvandy Amador Penichet Instituto de Biotecnología de las Plantas, Universidad Central “Marta Abreu" de Las Villas
  • Damny Magdaleno Guevara Departamento de Computación, Universidad Central “Marta Abreu" de Las Villas
  • María Matilde García Lorenzo Departamento de Computación, Universidad Central “Marta Abreu" de Las Villas

DOI:

https://doi.org/10.13053/cys-22-1-2763

Keywords:

Scientific paper, similarity function, clustering.

Abstract

The amount of scientific information available on the Internet, corporate intranets, and other media is growing rapidly. Managing knowledge from the information that can be found in scientific publications is essential for any researcher. The management of scientific information is increasingly more complex and challenging, since documents collections are generally heterogeneous, large, diverse and dynamic. Overcoming these challenges is essential to give to the scientists the best conditions to manage the time required to process scientific information. In this work, we implemented a new similarity’s function for scientific articles' clustering in based on the information provided by the references of the articles. The use of this function contributes significantly to discover relevant knowledge from scientific literature.

Author Biography

Lisvandy Amador Penichet, Instituto de Biotecnología de las Plantas, Universidad Central “Marta Abreu" de Las Villas

Reserva Científica, Dirección de Postgrado y Gestión de la Información.

Downloads

Published

2018-03-30

Issue

Vol. 22 No. 1 (2018): Thematic Issue on Language & Knowledge Engineering (Guest Editors: D. Pinto, D. Vilariño, B. Beltrán)

Section

Articles of the Thematic Issue

License 

Hereby I transfer exclusively to the Journal "Computación y 
Sistemas", published by the Computing Research Center (CIC-IPN),
the Copyright of the aforementioned paper. I also accept that these 
rights will not be transferred to any other publication, in any other 
format, language or other existing means of developing.
I certify that the paper has not been previously disclosed or simultaneo
usly submitted to any other publication, and that it does not contain 
material whose publication would violate the Copyright or other 
proprietary rights of any person, company or institution. I certify that 
I have the permission from the institution or company where I work or 
study to publish this work.
The representative author accepts the responsibility for the publication
of this paper on behalf of each and every one of the authors. 
This transfer is subject to the following conditions:
  • The authors retain all ownership rights (such as patent rights) of this work, except for the publishing rights transferred to the CIC, through this document.
  • Authors retain the right to publish the work in whole or in part in any book they are the authors or publishers. They can also make use of this work in conferences, courses, personal web pages, and so on.
  • Authors may include working as part of his thesis, for non-profit distribution only.