Joint Text Mining with Heterogeneous Data

2018 ◽  
pp. 235-258
Author(s):  
Charu C. Aggarwal
2021 ◽  
Author(s):  
Ester Alba ◽  
Mar Gaitán ◽  
Arabella León ◽  
Dunia Mladenic ◽  
Janez Branek

Abstract The cultural heritage domain in general and silk textiles, in particular, are characterized by large, rich and heterogeneous data sets. Silk heritage vocabulary comes from multiple sources that have been mixed up across time and space. This has led to the use of different terminology in specialized organizations in order to describe their artefacts. This makes data interoperability between independent catalogues very difficult. To address these issues, SILKNOW created a multilingual thesaurus related to silk textiles. It was carried out by experts in textile terminology and art historians and computationally implemented by experts in text mining, multi-/cross-linguality and semantic extraction from text. This paper presents the rationale behind the realization of this thesaurus.


2013 ◽  
Author(s):  
Ronald N. Kostoff ◽  
◽  
Henry A. Buchtel ◽  
John Andrews ◽  
Kirstin M. Pfiel

2020 ◽  
Vol 42 (5) ◽  
pp. 279-307
Author(s):  
Yonglim Joe
Keyword(s):  

2019 ◽  
Vol 19 (2) ◽  
pp. 29-38
Author(s):  
Young-Hee Kim ◽  
◽  
Taek-Hyun Lee ◽  
Jong-Myoung Kim ◽  
Won-Hyung Park ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document