TY  - JOUR
AU  - Jäschke, Robert
AU  - Marinho, Leandro
AU  - Hotho, Andreas
AU  - Schmidt-Thieme, Lars
AU  - Stumme, Gerd
T1  - Tag Recommendations in Folksonomies
JO  - 
PY  - 2007/
VL  - 
IS  - 
SP  - 
EP  - 
UR  - http://www.kde.cs.uni-kassel.de/hotho/pub/2007/kdml_recommender_final.pdf
DO  - 
KW  - bibsonomy del.icio.us folkrank folksonomy kassel last.fm nepomuk paper read:2008 recommendation tagging tagora uni
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SN  - 978-3-86010-907-6
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TY  - RPRT
AU  - Heymann, Paul
AU  - Garcia-Molina, Hector
A2  - 
T1  - Collaborative Creation of Communal Hierarchical Taxonomies in Social Tagging Systems
PB  - Computer Science Department
AD  - 
PY  - 2006/04
VL  - 
IS  - 2006-10
SP  - 
EP  - 
UR  - http://dbpubs.stanford.edu:8090/pub/2006-10
DO  - 
KW  - clustering collaborative communal connotea del.icio.us flickr folksonomy hierarchical paper read:2008 tagging taxonomy
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AB  - Collaborative tagging systems---systems where many casual users annotate objects with free-form strings (tags) of their choosing---have recently emerged as a powerful way to label and organize large collections of data. During our recent investigation into these types of systems, we discovered a simple but remarkably effective algorithm for converting a large corpus of tags annotating objects in a tagging system into a navigable hierarchical taxonomy of tags. We first discuss the algorithm and then present a preliminary model to explain why it is so effective in these types of systems.
ER  -

TY  - JOUR
AU  - Golder, Scott
AU  - Huberman, Bernardo A.
T1  - The Structure of Collaborative Tagging Systems
JO  - 
PY  - 2005/
VL  - 
IS  - 
SP  - 
EP  - 
UR  - http://www.citebase.org/abstract?id=oai:arXiv.org:cs/0508082
DO  - 
KW  - collaborative data del.icio.us folksonomy hierarchy kind-of-tags paper read:2008 structure tagging
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SN  - 
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AB  - Collaborative tagging describes the process by which many users add metadata in the form of keywords to shared content. Recently, collaborative tagging has grown in popularity on the web, on sites that allow users to tag bookmarks, photographs and other content. In this paper we analyze the structure of collaborative tagging systems as well as their dynamical aspects. Specifically, we discovered regularities in user activity, tag frequencies, kinds of tags used, bursts of popularity in bookmarking and a remarkable stability in the relative proportions of tags within a given url. We also present a dynamical model of collaborative tagging that predicts these stable patterns and relates them to imitation and shared knowledge.
ER  -