Logo des Repositoriums
 

Understanding the effects of temporal energy-data aggregation on clustering quality

dc.contributor.authorTrittenbach, Holger
dc.contributor.authorBach, Jakob
dc.contributor.authorBöhm, Klemens
dc.date.accessioned2021-06-21T12:14:13Z
dc.date.available2021-06-21T12:14:13Z
dc.date.issued2019
dc.description.abstractEnergy data often is available at high temporal resolution, which challenges the scalability of data-analysis methods. A common way to cope with this is to aggregate data to, say, 15-minute-interval summaries. But it often is not known how much information is lost with this, i. e., how good analysis results on aggregated data actually are. In this article, we study the effects of aggregating energy data on clustering. We propose an experimental design to compare a wide range of clustering methods found in literature. We then introduce different ways to compare clustering results obtained with different aggregation schemes. Our evaluation shows that aggregation affects the clustering quality significantly. Finally, we propose guidelines to select an aggregation scheme.en
dc.identifier.doi10.1515/itit-2019-0014
dc.identifier.pissn2196-7032
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/36648
dc.language.isoen
dc.publisherDe Gruyter
dc.relation.ispartofit - Information Technology: Vol. 61, No. 2-3
dc.subjectData mining
dc.subjectclustering
dc.subjectenergy data
dc.subjectaggregation
dc.subjectbenchmark
dc.titleUnderstanding the effects of temporal energy-data aggregation on clustering qualityen
dc.typeText/Journal Article
gi.citation.endPage123
gi.citation.publisherPlaceBerlin
gi.citation.startPage111

Dateien