| dc.contributor.author | Romberg, Julia | |
| dc.contributor.editor | Mitschang, Bernhard | |
| dc.contributor.editor | Nicklas, Daniela | |
| dc.contributor.editor | Leymann, Frank | |
| dc.contributor.editor | Schöning, Harald | |
| dc.contributor.editor | Herschel, Melanie | |
| dc.contributor.editor | Teubner, Jens | |
| dc.contributor.editor | Härder, Theo | |
| dc.contributor.editor | Kopp, Oliver | |
| dc.contributor.editor | Wieland, Matthias | |
| dc.date.accessioned | 2017-06-21T11:24:40Z | |
| dc.date.available | 2017-06-21T11:24:40Z | |
| dc.date.issued | 2017 | |
| dc.identifier.isbn | 978-3-88579-660-2 | |
| dc.identifier.issn | 1617-5468 | |
| dc.description.abstract | We draw a comparison on the behavior of several relevance feedback techniques on a corpus of German news articles. In contrast to the standard application of relevance feedback, no explicit user query is given and the main goal is to recognize a user’s preferences and interests in the examined data collection. The compared techniques are based on vector space models and probabilistic models. The results show that the performance is category-dependent on our data and that overall the vector space approach Ide performs best. | en |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-266 | |
| dc.subject | Relevance Feedback | |
| dc.subject | Text Mining | |
| dc.subject | Filtering Systems | |
| dc.title | Comparing Relevance Feedback Techniques on German News Articles | en |
| dc.type | Text/Conference Paper | |
| dc.pubPlace | Bonn | |
| mci.reference.pages | 301-310 | |
| mci.conference.sessiontitle | Studierendenprogramm | |
| mci.conference.location | Stuttgart | |
| mci.conference.date | 6.-10. März 2017 | |
