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A General Approach to Represent and Query Now-Relative Medical Data in Relational Databases

Contributo in Atti di convegno
Data di Pubblicazione:
2015
Abstract:
Now-related temporal data play an important role in the medical context. Current relational temporal database (TDB) approaches are limited since (i) they (implicitly) assume that the span of time occurring between the time when facts change in the world and the time when the changes are recorded in the database is exactly known, and (ii) do not explicitly provide an extended relational algebra to query now-related data. We propose an approach that, widely adopting AI symbolic manipulation techniques, overcomes the above limitations.
Tipologia CRIS:
04A-Conference paper in volume
Keywords:
temporal relational database, now-related data, temporal algebra
Elenco autori:
Anselma, Luca; Piovesan, Luca; Sattar, Abdul; Stantic, Bela; Terenziani, Paolo
Autori di Ateneo:
ANSELMA Luca
Link alla scheda completa:
https://iris.unito.it/handle/2318/1521947
Link al Full Text:
https://iris.unito.it/retrieve/handle/2318/1521947/168028/AIME_short_final_4aperto.pdf
Titolo del libro:
Artificial Intelligence in Medicine
Pubblicato in:
LECTURE NOTES IN COMPUTER SCIENCE
Journal
LECTURE NOTES IN COMPUTER SCIENCE
Series
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Dati Generali

URL

http://link.springer.com/chapter/10.1007%2F978-3-319-19551-3_41
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