SciELO - Scientific Electronic Library Online

vol.22 issue1Generating Aspect-based Extractive Opinion Summary: Drawing Inferences from Social Media TextsInferences for Enrichment of Collocation Databases by Means of Semantic Relations author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand




Related links

  • Have no similar articlesSimilars in SciELO


Computación y Sistemas

Print version ISSN 1405-5546


AMADOR PENICHET, Lisvandy; MAGDALENO GUEVARA, Damny  and  GARCIA LORENZO, Maria Magdalena. New Similarity Function for Scientific Articles Clustering based on the Bibliographic References. Comp. y Sist. [online]. 2018, vol.22, n.1, pp.93-102. ISSN 1405-5546.

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.

Keywords : Scientific paper; similarity function; clustering.

        · text in English     · English ( pdf )