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Prethodno priopćenje

https://doi.org/10.31664/zu.2019.105.07

ArchiText Mining: Applying Text Analytics to Research on Modern Architecture

Ana Esteban-Maluenda ; Arhitektonski fakultet, Politehničko sveučilište u Madridu, Madrid, Španjolska
Laura Sánchez Carrasco ; Arhitektonski fakultet, Politehničko sveučilište u Madridu, Madrid, Španjolska
Luis San Pablo Moreno ; nezavisni istraživač, Madrid, Španjolska


Puni tekst: hrvatski pdf 1.351 Kb

str. 158-179

preuzimanja: 325

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Puni tekst: engleski pdf 1.351 Kb

str. 158-179

preuzimanja: 345

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Sažetak

ArchiteXt Mining: Spanish Modern Architecture through Its Texts (1939–1975) is a research project funded by the Government of Spain through the 2015 Call for “Excellence Projects” of the Ministry of Economy and Competitiveness. This project aims to explore a new viewpoint and look into the special features of Spanish modern architecture. Despite the increasing success of using data analysis as a tool in a variety of disciplines, research on architectural theory has never made the most efficient use of these technologies. The Spanish and international circumstances of modern architecture development have been scrutinized through qualitative research, which has established a shared theoretical ground. It is now time to start a new in-depth research based on objective data. To address this challenge, we propose the application of text mining techniques to take advantage of the best data source in the field: architectural periodicals. The purpose is to create a powerful database hosted on a public website for the scientific community. Thus, this project fulfils several e-Research objectives: to facilitate the computerization of data research, to support every stageof data collection, and to manage big data analyses with thehelp of specific tools.

Ključne riječi

architectural periodicals; text mining; Spanish modern architecture; data analysis

Hrčak ID:

233175

URI

https://hrcak.srce.hr/233175

Datum izdavanja:

1.12.2019.

Podaci na drugim jezicima: hrvatski

Posjeta: 1.899 *