Data Analytics with Graph Algorithms – A Hands-on Tutorial with Neo4J
| dc.contributor.author | Wiese, Lena | |
| 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 | 2019-04-15T11:40:35Z | |
| dc.date.available | 2019-04-15T11:40:35Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | This tutorial presents perspectives for advanced graph data analytics and covers the background of graph data management in modern data stores. It provides an overview of several well-established graph algorithms. The three categories covered are path-based algorithms, community detection and centrality scores. A deeper understanding of graph algorithms is a major precondition to efficiently analyze graph-structured data. The tutorial hence enables participants to achieve an informed decision about what kind of algorithm is appropriate for which use case. | en |
| dc.identifier.doi | 10.18420/btw2019-ws-26 | |
| dc.identifier.isbn | 978-3-88579-684-8 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/21813 | |
| 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.title | Data Analytics with Graph Algorithms – A Hands-on Tutorial with Neo4J | en |
| gi.citation.endPage | 261 | |
| gi.citation.startPage | 259 | |
| gi.conference.date | 4.-8. März 2019 | |
| gi.conference.location | Rostock | |
| gi.conference.sessiontitle | Tutorienprogramm |
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