ForCE: Is Estimation of Data Completeness Through Time Series Forecasts Feasible?

Beitrag bei einer Tagung
(Originalarbeit)


Details zur Publikation

Autor(en): Endler G, Baumgärtel P, Wahl AM, Lenz R
Verlag: Springer
Verlagsort: Switzerland
Jahr der Veröffentlichung: 2015
Titel der Reihe: Lecture Notes in Computer Science
Heftnummer: 9282
Tagungsband: Advances in Databases and Information Systems
Seitenbereich: 261-274
ISBN: 978-3-319-23134-1
ISSN: 0302-9743


Abstract


Measuring the completeness of a data population often requires either expert knowledge or the presence of reference data. If neither is available, measuring population completeness becomes nontrivial. We present the ForCE approach (Forecasting for Completeness Estimation), a method to estimate the completeness of timestamped data using time series forecasting. We evaluate the method’s feasibility using a medical domain real-world dataset, which we provide for download. The method is compared to three baselines. ForCE manages to surpass all three.



FAU-Autoren / FAU-Herausgeber

Baumgärtel, Philipp
Lehrstuhl für Informatik 6 (Datenmanagement)
Endler, Gregor
Lehrstuhl für Informatik 6 (Datenmanagement)
Lenz, Richard Prof. Dr.-Ing.
Professur für Informatik (Datenbanksysteme)
Wahl, Andreas Maximilian
Lehrstuhl für Informatik 6 (Datenmanagement)


Zitierweisen

APA:
Endler, G., Baumgärtel, P., Wahl, A.M., & Lenz, R. (2015). ForCE: Is Estimation of Data Completeness Through Time Series Forecasts Feasible? In Advances in Databases and Information Systems (pp. 261-274). Futuroscope, Poitiers - France, FR: Switzerland: Springer.

MLA:
Endler, Gregor, et al. "ForCE: Is Estimation of Data Completeness Through Time Series Forecasts Feasible?" Proceedings of the ADBIS 2015, Futuroscope, Poitiers - France Switzerland: Springer, 2015. 261-274.

BibTeX: 

Zuletzt aktualisiert 2018-23-11 um 06:04