| dc.contributor.author | Rost, Christopher | |
| dc.contributor.author | Thor, Andreas | |
| dc.contributor.author | Rahm, Erhard | |
| dc.contributor.editor | Meyer, Holger | |
| dc.contributor.editor | Ritter, Norbert | |
| dc.contributor.editor | Thor, Andreas | |
| dc.contributor.editor | Nicklas, Daniela | |
| dc.contributor.editor | Heuer, Andreas | |
| dc.contributor.editor | Klettke, Meike | |
| dc.date.accessioned | 2019-04-15T11:40:29Z | |
| dc.date.available | 2019-04-15T11:40:29Z | |
| dc.date.issued | 2019 | |
| dc.identifier.isbn | 978-3-88579-684-8 | |
| dc.identifier.issn | 1617-5468 | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/21797 | |
| dc.description.abstract | The temporal analysis of evolving graphs is an important requirement in many domains but hardly supported in current graph database and graph processing systems. We therefore have started with extending Gradoop for temporal graph analysis by adding time properties to vertices, edges and graphs and using them within graph operators. We outline these extensions and show their use in a bibliographic scenario to analyze temporal citation patterns. | en |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik, Bonn | |
| dc.relation.ispartof | BTW 2019 – Workshopband | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) – Proceedings, Volume P-290 | |
| dc.subject | Temporal Graph | |
| dc.subject | Temporal Graph Data Model | |
| dc.subject | Graph Analysis | |
| dc.title | Temporal Graph Analysis using Gradoop | en |
| mci.reference.pages | 109-118 | |
| mci.conference.sessiontitle | Workshop on Big (and Small) Data in Science and Humanities (BigDS 2019) | |
| mci.conference.location | Rostock | |
| mci.conference.date | 4.-8. März 2019 | |
| dc.identifier.doi | 10.18420/btw2019-ws-11 | |
