- Titel
- Designing Random Sample Synopses with Outliers
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:14-qucosa2-803832
- Konferenz
- IEEE 24th International Conference on Data Engineering. Cancun, 07.-12.04.2008
- Quellenangabe
- 2008 IEEE 24th International Conference on Data Engineering : Proceedings
Erscheinungsort: New York, NY
Verlag: Institute of Electrical and Electronics Engineers incorporated (IEEE)
Erscheinungsjahr: 2008
Seiten: 1400-1402
ISBN: 978-1-4244-1836-7 - Erstveröffentlichung
- 2008
- Abstract (EN)
- Random sampling is one of the most widely used means to build synopses of large datasets because random samples can be used for a wide range of analytical tasks. Unfortunately, the quality of the estimates derived from a sample is negatively affected by the presence of 'outliers' in the data. In this paper, we show how to circumvent this shortcoming by constructing outlier-aware sample synopses. Our approach extends the well-known outlier indexing scheme to multiple aggregation columns.
- Andere Ausgabe
- Link zum Artikel, der zuerst in der IEEE Xplore Digital Library erschienen ist:
DOI: 10.1109/ICDE.2008.4497569 - Freie Schlagwörter (DE)
- Aggregate, Schätzfehler, Stichprobenverfahren, Indizierung, Abfrageverarbeitung Informatik, Großsysteme, Streaming Media, Datenanalyse, Bilddatenbanken
- Freie Schlagwörter (EN)
- Aggregates, Estimation error, Sampling methods, Indexing, Query processing Computer science, Large-scale systems, Streaming media, Data analysis, Image databases
- Klassifikation (DDC)
- 004
- Verlag
- IEEE, New York, NY
- Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:14-qucosa2-803832
- Veröffentlichungsdatum Qucosa
- 12.08.2022
- Dokumenttyp
- Konferenzbeitrag
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
