Skip to Main Content (Press Enter)

Logo UNIPV
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture

UNIFIND
Logo UNIPV

|

UNIFIND

unipv.it
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Professioni
  • Persone
  • Pubblicazioni
  • Strutture
  1. Pubblicazioni

Automated Classification Using Linked Open Data. A Case Study on Faceted Classification and Wikidata

Articolo
Data di Pubblicazione:
2021
Abstract:
The newly created Wikidata gadget, CCLitBox, for the automated classification of literary authors and works by a faceted classification and using Linked Open Data (LOD) is presented. The tool - whose scripts are available on Wikidata for free for any Wikimedia user on the platform and published on Zenodo - was created by Phyton programming language. It reproduces the classification algorithm of class O Literature of the Colon Classification and applies it using data freely available in Wikidata to create Colon Classification class numbers. CCLitBox is totally free and enables any user to classify literary authors and their works; it is easily accessible to everybody; it uses LOD from Wikidata but missing data for classification can be freely added if necessary; it is readymade for any cooperative and networked project. The paper was presented during a conference at the SRELS, India, the Endowment founded by S.R. Ranganathan, the creator of the Colon Classification, on which the original idea of the automated classification was based. The paper was requested and published in an updated and enlarged version on the SRELS Journal (SRELS JOURNAL OF INFORMATION MANAGEMENT) in 2023, DOI: https://doi.org/10.17821/srels/2023/v60i3/171024
Tipologia CRIS:
1.1 Articolo in rivista
Keywords:
Automated classification, Wikidata, linked open data, faceted classification, Colon Classification, literature
Elenco autori:
Bianchini, Carlo; Bargioni, Stefano
Autori di Ateneo:
BIANCHINI CARLO
Link alla scheda completa:
https://iris.unipv.it/handle/11571/1511096
Pubblicato in:
CATALOGING & CLASSIFICATION QUARTERLY
Journal
  • Dati Generali

Dati Generali

URL

https://www.tandfonline.com/doi/full/10.1080/01639374.2021.1977447
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 26.2.4.0