| dc.contributor.author | Egger, Marc | |
| dc.contributor.author | Lang, André | |
| dc.date | 2013-02-01 | |
| dc.date.accessioned | 2018-01-08T09:16:22Z | |
| dc.date.available | 2018-01-08T09:16:22Z | |
| dc.date.issued | 2013 | |
| dc.identifier.issn | 1610-1987 | |
| dc.identifier.uri | http://dl.gi.de/handle/20.500.12116/11330 | |
| dc.description.abstract | In this brief tutorial, we provide an overview of investigating text-based user-generated content for information that is relevant in the corporate context. We structure the overall process along three stages: collection, analysis, and visualization. Corresponding to the stages we outline challenges and basic techniques to extract information of different levels of granularity. | |
| dc.publisher | Springer | |
| dc.relation.ispartof | KI - Künstliche Intelligenz: Vol. 27, No. 1 | |
| dc.relation.ispartofseries | KI - Künstliche Intelligenz | |
| dc.subject | Information extraction | |
| dc.subject | Natural language processing | |
| dc.subject | Opinion mining | |
| dc.subject | Text mining | |
| dc.subject | Web mining | |
| dc.title | A Brief Tutorial on How to Extract Information from User-Generated Content (UGC) | |
| dc.type | Text/Journal Article | |
| mci.reference.pages | 53-60 | |
| gi.identifier.doi | 10.1007/s13218-012-0224-1 | |
