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

Conference contribution
(Original article)


Publication Details

Author(s): Endler G, Baumgärtel P, Wahl AM, Lenz R
Publisher: Springer
Publishing place: Switzerland
Publication year: 2015
Title of series: Lecture Notes in Computer Science
Journal issue: 9282
Conference Proceedings Title: Advances in Databases and Information Systems
Pages range: 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 Authors / FAU Editors

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


How to cite

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: 

Last updated on 2018-19-04 at 03:04