Small World Folksonomies: Clustering in Tri-Partite Hypergraphs
| dc.date.accessioned | 2006-12-04T09:37:44Z | |
| dc.date.available | 2006-12-04T09:37:44Z | |
| dc.date.issued | 2006-12-04T09:37:44Z | |
| dc.identifier.uri | urn:nbn:de:hebis:34-2006120415997 | |
| dc.identifier.uri | http://hdl.handle.net/123456789/2006120415997 | |
| dc.format.extent | 190154 bytes | |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | eng | |
| dc.rights | Urheberrechtlich geschützt | |
| dc.rights.uri | https://rightsstatements.org/page/InC/1.0/ | |
| dc.subject | Folksonomies | eng |
| dc.subject | Web 2.0 | eng |
| dc.subject | Small Worlds | eng |
| dc.subject.ddc | 004 | |
| dc.title | Small World Folksonomies: Clustering in Tri-Partite Hypergraphs | eng |
| dc.type | Technischer Report | |
| dcterms.abstract | Many recent Web 2.0 resource sharing applications can be subsumed under the "folksonomy" moniker. Regardless of the type of resource shared, all of these share a common structure describing the assignment of tags to resources by users. In this report, we generalize the notions of clustering and characteristic path length which play a major role in the current research on networks, where they are used to describe the small-world effects on many observable network datasets. To that end, we show that the notion of clustering has two facets which are not equivalent in the generalized setting. The new measures are evaluated on two large-scale folksonomy datasets from resource sharing systems on the web. | eng |
| dcterms.accessRights | open access | |
| dcterms.creator | Schmitz, Christoph | |
| dcterms.isPartOf | Kasseler Informatikschriften ;; 02 | ger |
| dc.subject.swd | Informatik | ger |
| dc.subject.swd | Graphentheorie | ger |
| dc.subject.swd | Data Mining | eng |
| dc.subject.swd | World Wide Web | eng |
| dcterms.source.series | Kasseler Informatikschriften | ger |
| dcterms.source.volume | 02 | ger |
