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Automatic Bookmark Classification - A Collaborative Approach

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

In: Proceedings of the 2nd Workshop in Innovations in Web Infrastructure IWI2 at WWW2006 Edinburgh, Scotland: (May 2006) .

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URL:	http://www.kde.cs.uni-kassel.de/pub/pdf/benz2006automatic.pdf
Additional URLs:	Workshop website URL:text:

Bookmarks or Favorites, Hotlists are a popular strategy to relocate interesting websites on the WWW by creating a personalized local URL repository. Most current browsers offer a facility to store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable taxonomy. 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-neighbour-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. Additionally, a procedure to generate keyword recommendations is proposed to ease the annotation of new bookmarks. A prototype system called CariBo has been implemented as a plugin of the central bookmark server software SiteBar. A case study conducted with real user data supports the validity of the approach.

BibTeX record

@inproceedings{benz2006automatic,
  abstract = {Bookmarks (or Favorites, Hotlists) are a popular strategy to relocate interesting websites on the WWW by creating a personalized local URL repository. Most current browsers offer a facility to store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable taxonomy. 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-neighbour-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. Additionally, a procedure to generate keyword recommendations is proposed to ease the annotation of new bookmarks. A prototype system called CariBo has been implemented as a plugin of the central bookmark server software SiteBar. A case study conducted with real user data supports the validity of the approach.},
  added-at = {2011-01-28T16:26:42.000+0100},
  address = {Edinburgh, Scotland},
  author = {Benz, Dominik and Tso, Karen H. L. and Schmidt-Thieme, Lars},
  biburl = {http://www.bibsonomy.org/bibtex/29d685c05008804a45b72a43586777b3b/dbenz},
  booktitle = {Proceedings of the 2nd Workshop in Innovations in Web Infrastructure (IWI2) at WWW2006},
  file = {benz2006automatic.pdf:benz2006automatic.pdf:PDF},
  interhash = {72efbe1b69d12bc3ce35522bc1c83e82},
  intrahash = {9d685c05008804a45b72a43586777b3b},
  keywords = {studienarbeit www2006 2006 myown iwi itegpub},
  month = May,
  note = {isbn = {085432853X}},
  timestamp = {2011-01-28T16:26:42.000+0100},
  title = {Automatic Bookmark Classification - A Collaborative Approach},
  url = {http://www.kde.cs.uni-kassel.de/pub/pdf/benz2006automatic.pdf},
  year = 2006
}

Endnote record

%0 Conference Paper
%1 benz2006automatic
%A Benz, Dominik
%A Tso, Karen H. L.
%A Schmidt-Thieme, Lars
%B Proceedings of the 2nd Workshop in Innovations in Web Infrastructure (IWI2) at WWW2006
%C Edinburgh, Scotland
%D 2006
%K 
%T Automatic Bookmark Classification - A Collaborative Approach
%U http://www.kde.cs.uni-kassel.de/pub/pdf/benz2006automatic.pdf
%X Bookmarks (or Favorites, Hotlists) are a popular strategy to relocate interesting websites on the WWW by creating a personalized local URL repository. Most current browsers offer a facility to store and manage bookmarks in a hierarchy of folders; though, with growing size, users reportedly have trouble to create and maintain a stable taxonomy. 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-neighbour-classifiers is used to derive a recommendation from similar users on where to store a new bookmark. Additionally, a procedure to generate keyword recommendations is proposed to ease the annotation of new bookmarks. A prototype system called CariBo has been implemented as a plugin of the central bookmark server software SiteBar. A case study conducted with real user data supports the validity of the approach.

BibSonomy :: publication ::

Automatic Bookmark Classification - A Collaborative Approach

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Abstract

BibTeX record

Endnote record