%0 Journal Article %1 1290825 %A Benz, Dominik %A Tso, Karen H. L. %A Schmidt-Thieme, Lars %C New York, NY, USA %D 2007 %I Elsevier North-Holland, Inc. %J Comput. Networks %K folksonomy iim_socsoft imported recommendation %N 16 %P 4574--4585 %R http://dx.doi.org/10.1016/j.comnet.2007.06.014 %T Supporting collaborative hierarchical classification: Bookmarks as an example %U http://portal.acm.org/citation.cfm?id=1290825&coll=Portal&dl=GUIDE&CFID=46454031&CFTOKEN=27530397 %V 51 %X 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.

@article{1290825, 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.}, added-at = {2008-01-10T16:46:04.000+0100}, address = {New York, NY, USA}, author = {Benz, Dominik and Tso, Karen H. L. and Schmidt-Thieme, Lars}, biburl = {https://www.bibsonomy.org/bibtex/2ced5849c3ca3d519dd6a0ada13ee49bd/ewomant}, description = {Supporting collaborative hierarchical classification}, doi = {http://dx.doi.org/10.1016/j.comnet.2007.06.014}, interhash = {181404c6a55baf6fe5db8448ac0d5bf0}, intrahash = {ced5849c3ca3d519dd6a0ada13ee49bd}, issn = {1389-1286}, journal = {Comput. Networks}, keywords = {folksonomy iim_socsoft imported recommendation}, number = 16, pages = {4574--4585}, publisher = {Elsevier North-Holland, Inc.}, timestamp = {2008-01-24T16:18:20.000+0100}, title = {Supporting collaborative hierarchical classification: Bookmarks as an example}, url = {http://portal.acm.org/citation.cfm?id=1290825&coll=Portal&dl=GUIDE&CFID=46454031&CFTOKEN=27530397}, volume = 51, year = 2007 }