The Borda Social Choice Movie Recommender
| dc.contributor.author | Kastner, Johannes | |
| dc.contributor.author | Ranitovic, Nemanja | |
| dc.contributor.author | Endres, Markus | |
| dc.contributor.editor | Grust, Torsten | |
| dc.contributor.editor | Naumann, Felix | |
| dc.contributor.editor | Böhm, Alexander | |
| dc.contributor.editor | Lehner, Wolfgang | |
| dc.contributor.editor | Härder, Theo | |
| dc.contributor.editor | Rahm, Erhard | |
| dc.contributor.editor | Heuer, Andreas | |
| dc.contributor.editor | Klettke, Meike | |
| dc.contributor.editor | Meyer, Holger | |
| dc.date.accessioned | 2019-04-11T07:21:28Z | |
| dc.date.available | 2019-04-11T07:21:28Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | In this demo paper we present a recommender system, which exploits the Borda social choice voting rule for clustering recommendations in order to produce comprehensible results for a user. Considering existing clustering techniques like k-means, the overhead of normalizing and preparing the preferred user data is dropped. In our demo showcase we facilitate a comparison of our clustering approach to the well known k-means++ with traditional distance measures. | en |
| dc.identifier.doi | 10.18420/btw2019-31 | |
| dc.identifier.isbn | 978-3-88579-683-1 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/21717 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik, Bonn | |
| dc.relation.ispartof | BTW 2019 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) – Proceedings, Volume P-289 | |
| dc.subject | Clustering | |
| dc.subject | k-means | |
| dc.subject | Borda | |
| dc.subject | Social choice | |
| dc.title | The Borda Social Choice Movie Recommender | en |
| gi.citation.endPage | 502 | |
| gi.citation.startPage | 499 | |
| gi.conference.date | 4.-8. März 2019 | |
| gi.conference.location | Rostock | |
| gi.conference.sessiontitle | Demonstrationen |
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