Enhancing business intelligence with unstructured data
| dc.contributor.author | Lang, Alexander | |
| dc.contributor.author | Mera Ortiz, Maria | |
| dc.contributor.author | Abraham, Stefan | |
| dc.contributor.editor | Freytag, Johann-Christoph | |
| dc.contributor.editor | Ruf, Thomas | |
| dc.contributor.editor | Lehner, Wolfgang | |
| dc.contributor.editor | Vossen, Gottfried | |
| dc.date.accessioned | 2019-02-20T10:28:13Z | |
| dc.date.available | 2019-02-20T10:28:13Z | |
| dc.date.issued | 2009 | |
| dc.description.abstract | Quality early warning and proactive customer churn detection are two examples of applications that can benefit from insights gained from unstructured text data. The term "Unstructured Business Intelligence" describes methods and tools that enable data war | en |
| dc.identifier.isbn | 978-3-88579-238-3 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/20467 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Datenbanksysteme in Business, Technologie und Web (BTW) – 13. Fachtagung des GI-Fachbereichs "Datenbanken und Informationssysteme" (DBIS) | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-144 | |
| dc.title | Enhancing business intelligence with unstructured data | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 485 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 469 | |
| gi.conference.date | 2.-6. März 2009 | |
| gi.conference.location | Münster | |
| gi.conference.sessiontitle | Regular Research Papers |
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