New technologies for the conservation and preservation of cultural heritage through a bibliometric analysis

被引:5
作者
Prados-Pena, Maria Belen [1 ]
Pavlidis, George [2 ]
Garcia-Lopez, Ana [3 ]
机构
[1] Univ Granada, Fac Econ & Business Sci, Granada, Spain
[2] Athena Res & Innovat Ctr Informat Commun & Knowle, Athens, Greece
[3] Univ Granada, Alonso Cano Fac Fine Arts, Granada, Spain
关键词
Machine learning; Artificial intelligence; Cultural heritage; Conservation; MACHINE-LEARNING APPROACH; TOURISM; MANAGEMENT; EFFICIENT; PATTERNS;
D O I
10.1108/JCHMSD-07-2022-0124
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Purpose This study aims to analyze the impact of Artificial Intelligence (AI) and Machine Learning (ML) on heritage conservation and preservation, and to identify relevant future research trends, by applying scientometrics.Design/methodology/approach A total of 1,646 articles, published between 1985 and 2021, concerning research on the application of ML and AI in cultural heritage were collected from the Scopus database and analyzed using bibliometric methodologies.Findings The findings of this study have shown that although there is a very important increase in academic literature in relation to AI and ML, publications that specifically deal with these issues in relation to cultural heritage and its conservation and preservation are significantly limited.Originality/value This study enriches the academic outline by highlighting the limited literature in this context and therefore the need to advance the study of AI and ML as key elements that support heritage researchers and practitioners in conservation and preservation work.
引用
收藏
页码:664 / 686
页数:23
相关论文
共 51 条
[1]   Co-authorship in management and organizational studies: An empirical and network analysis [J].
Acedo, Francisco Jose ;
Barroso, Carmen ;
Casanueva, Cristobal ;
Galan, Jose Luis .
JOURNAL OF MANAGEMENT STUDIES, 2006, 43 (05) :957-983
[2]   Comparison and ranking of different modelling techniques for prediction of site index in Mediterranean mountain forests [J].
Aertsen, Wim ;
Kint, Vincent ;
van Orshoven, Jos ;
Ozkan, Kuersad ;
Muys, Bart .
ECOLOGICAL MODELLING, 2010, 221 (08) :1119-1130
[3]   Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies [J].
Baas, Jeroen ;
Schotten, Michiel ;
Plume, Andrew ;
Cote, Gregoire ;
Karimi, Reza .
QUANTITATIVE SCIENCE STUDIES, 2020, 1 (01) :377-386
[4]   Image restoration of arbitrarily warped documents [J].
Brown, MS ;
Seales, WB .
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2004, 26 (10) :1295-1306
[5]   On the Mathematical Properties of the Structural Similarity Index [J].
Brunet, Dominique ;
Vrscay, Edward R. ;
Wang, Zhou .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2012, 21 (04) :1488-1499
[6]  
Carbone F, 2016, EUR J TOUR RES, V14, P75
[7]   A two-stage method for spectral-spatial classification of hyperspectral images [J].
Chan, Raymond H. ;
Kan, Kelvin K. ;
Nikolova, Mila ;
Plemmons, Robert J. .
JOURNAL OF MATHEMATICAL IMAGING AND VISION, 2020, 62 (6-7) :790-807
[8]   Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization [J].
Chan, RH ;
Ho, CW ;
Nikolova, M .
IEEE TRANSACTIONS ON IMAGE PROCESSING, 2005, 14 (10) :1479-1485
[9]   CiteSpace II: Detecting and visualizing emerging trends and transient patterns in scientific literature [J].
Chen, CM .
JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 2006, 57 (03) :359-377
[10]   Modeling heating and cooling loads by artificial intelligence for energy-efficient building design [J].
Chou, Jui-Sheng ;
Bui, Dac-Khuong .
ENERGY AND BUILDINGS, 2014, 82 :437-446