Understanding the evolution of science: analyzing evolving term co-occurrence graphs with spectral techniques - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Document Associé À Des Manifestations Scientifiques Année : 2019

Understanding the evolution of science: analyzing evolving term co-occurrence graphs with spectral techniques

Résumé

Given the high number of scientific papers that are published every year, it is a challenge to observe the evolution of scientific fields. While, for example, computer science and biology were considered rather unrelated 40 years ago, today, bioinformatics is a well-established field. One way to analyze these questions is to observe the evolution of the term co-occurrence graphs of the abstracts of scientific publications. In a term co-occurrence graph, two terms are connected if they appear together in an abstract of a publication. We weight the edges of this graph with the number of common occurrences. We analyze the evolution of this co-occurrence graph, that we constructed for each year, on the basis of a large collection of scientific articles, with the help of spectral techniques. We present our preliminary observations and discuss our ongoing work.
Fichier principal
Vignette du fichier
leg2019_Miklos_cameraRady.pdf (1.7 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-02195026 , version 1 (26-07-2019)

Identifiants

  • HAL Id : hal-02195026 , version 1

Citer

Zoltan Miklos, Mickaël Foursov, Franklin Lia, Ian Jeantet, David Gross-Amblard. Understanding the evolution of science: analyzing evolving term co-occurrence graphs with spectral techniques. Third international workshop on advances on managing and mining evolving graphs (LEG@ECMLPKDD), Sep 2019, Würzburg, Germany. ⟨hal-02195026⟩
141 Consultations
77 Téléchargements

Partager

Gmail Facebook X LinkedIn More