Topic modelling characterization of Mudejar art based on document titles Articles uri icon

publication date

  • September 2018

start page

  • 529

end page

  • 539

issue

  • 3

volume

  • 33

International Standard Serial Number (ISSN)

  • 2055-7671

Electronic International Standard Serial Number (EISSN)

  • 2055-768X

abstract

  • Text mining techniques were applied to a corpus consisting in the titles of 2,454 documents on Mudejar art, a style unique to Spanish art history. Probabilistic topic modelling was used to analyse the semantic structure underlying the suite of documents studied. Two classifications were obtained, an initial, generic division into five topics followed by a second more refined division into ten. These were compared to the preliminary subject categories found for the corpus with the guidance of an area specialist. The classifications delivered by the automatic and manual procedures were observed to be compatible. The conclusion drawn was that the deployment of digitized data affords the opportunity to conduct humanities studies from new perspectives.

subjects

  • Art
  • Library Science and Documentation

keywords

  • probabilistictopic modelling; mudejar art; bibliographic repertories; publication titles; arte mudéjar