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Visions and open challenges for a knowledge-based culturomics

Nina Tahmasebi ; Lars Borin ; Gabriele Capannini (Institutionen för data- och informationsteknik (Chalmers)) ; Devdatt Dubhashi (Institutionen för data- och informationsteknik, Datavetenskap (Chalmers)) ; Peter Exner ; Markus Forsberg ; Gerhard Gossen ; Fredrik Johansson (Institutionen för data- och informationsteknik, Datavetenskap (Chalmers)) ; Richard Johansson ; Mikael Kågebäck (Institutionen för data- och informationsteknik, Datorteknik (Chalmers)) ; Olof Mogren (Institutionen för data- och informationsteknik, Datavetenskap, Algoritmer (Chalmers)) ; Pierre Nugues ; Thomas Risse
International Journal on Digital Libraries (1432-5012). Vol. 15 (2015), 2-4, p. 169-187.
[Artikel, refereegranskad vetenskaplig]

The concept of culturomics was born out of the availability of massive amounts of textual data and the interest to make sense of cultural and language phenomena over time. Thus far however, culturomics has only made use of, and shown the great potential of, statistical methods. In this paper, we present a vision for a knowledge-based culturomics that complements traditional culturomics. We discuss the possibilities and challenges of combining knowledge-based methods with statistical methods and address major challenges that arise due to the nature of the data; diversity of sources, changes in language over time as well as temporal dynamics of information in general. We address all layers needed for knowledge-based culturomics, from natural language processing and relations to summaries and opinions.

Nyckelord: Culturomics, Statistical analysis, Knowledge-based analysis, Temporal text analysis, Digital humanities, eScience, eInfrastructure, Natural language processing



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Denna post skapades 2015-02-23. Senast ändrad 2016-07-07.
CPL Pubid: 212969

 

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