Name
Abstract | ||
|---|---|---|
Bookmarks (or favorites, hotlists) are popular strategies to relocate interesting websites on the WWW by creating a personalized URL repository. Most current browsers offer a facility to locally store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable organization structure. This paper presents a novel collaborative approach to ease bookmark management, especially the ''classification'' of new bookmarks into a folder. We propose a methodology to realize the collaborative classification idea of considering how similar users have classified a bookmark. A combination of nearest-neighbor-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. A prototype system called CariBo has been implemented as a plugin for the central bookmark server software SiteBar. All findings have been evaluated on a reasonably large scale, real user dataset with promising results, and possible implications for shared and social bookmarking systems are discussed. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.comnet.2007.06.014 | Computer Networks |
Keywords | DocType | Volume |
WWW,Social bookmarking,Bookmark classification,Collaborative filtering,Recommender systems | Journal | 51 |
Issue | ISSN | Citations |
16 | Computer Networks | 2 |
PageRank | References | Authors |
0.39 | 10 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dominik Benz | 1 | 500 | 21.61 |
| Karen H. L. Tso | 2 | 32 | 3.81 |
| Lars Schmidt-Thieme | 3 | 3802 | 216.58 |