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.
%0 Report
%1 heymann2006collaborative
%A Heymann, Paul
%A Garcia-Molina, Hector
%D 2006
%I Stanford
%K algorithm learning ontology
%N 2006-10
%T Collaborative Creation of Communal Hierarchical Taxonomies in Social Tagging Systems
%U http://ilpubs.stanford.edu:8090/775/
%X 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.
@techreport{heymann2006collaborative,
abstract = {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.},
added-at = {2017-05-02T09:22:32.000+0200},
author = {Heymann, Paul and Garcia-Molina, Hector},
biburl = {https://www.bibsonomy.org/bibtex/23b4ce6fd7fa6dbf1c39fd261fa39fcd6/thoni},
institution = {Stanford InfoLab},
interhash = {d77846b40aadb0e25233cabf905bb93e},
intrahash = {3b4ce6fd7fa6dbf1c39fd261fa39fcd6},
keywords = {algorithm learning ontology},
month = {April},
number = {2006-10},
publisher = {Stanford},
timestamp = {2017-05-02T09:22:32.000+0200},
title = {Collaborative Creation of Communal Hierarchical Taxonomies in Social Tagging Systems},
type = {Technical Report},
url = {http://ilpubs.stanford.edu:8090/775/},
year = 2006
}