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Supporting Collaborative Hierarchical Classification: Bookmarks as an Example

by: Dominik Benz, Karen H. L. Tso, and Lars Schmidt-Thieme

In: Special Issue of the Computer Networks journal on Innovations in Web Communications Infrastructure, Vol. 51, Nr. 16 (2007) , p. 4574--4585.

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URL:	http://www.kde.cs.uni-kassel.de/pub/pdf/benz2007supporting.pdf
DOI:	10.1016/j.comnet.2007.06.014
Additional URLs:	ACM reference URL:text:

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.

BibTeX record

@article{benz2007supporting,
  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 = {2011-01-28T16:26:42.000+0100},
  author = {Benz, Dominik and Tso, Karen H. L. and Schmidt-Thieme, Lars},
  biburl = {http://www.bibsonomy.org/bibtex/2ec4387ab22950b38a0c152d4f33b0987/dbenz},
  doi = {http://dx.doi.org/10.1016/j.comnet.2007.06.014},
  file = {benz2007supporting.pdf:benz2007supporting.pdf:PDF},
  interhash = {181404c6a55baf6fe5db8448ac0d5bf0},
  intrahash = {ec4387ab22950b38a0c152d4f33b0987},
  journal = {Special Issue of the Computer Networks journal on Innovations in Web Communications Infrastructure},
  keywords = {studienarbeit 2007 myown itegpub},
  number = 16,
  pages = {4574--4585},
  timestamp = {2011-01-28T16:26:42.000+0100},
  title = {Supporting Collaborative Hierarchical Classification: Bookmarks as an Example},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2007supporting.pdf},
  volume = 51,
  year = 2007
}

Endnote record

%0 Journal Article
%1 benz2007supporting
%A Benz, Dominik
%A Tso, Karen H. L.
%A Schmidt-Thieme, Lars
%D 2007
%J Special Issue of the Computer Networks journal on Innovations in Web Communications Infrastructure
%K 
%N 16
%P 4574--4585
%T Supporting Collaborative Hierarchical Classification: Bookmarks as an Example
%R http://dx.doi.org/10.1016/j.comnet.2007.06.014
%U http://www.kde.cs.uni-kassel.de/pub/pdf/benz2007supporting.pdf
%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.

BibSonomy :: publication ::

Supporting Collaborative Hierarchical Classification: Bookmarks as an Example

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Abstract

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Endnote record