Abstract In this paper, we evaluate the effectiveness of a semantic smoothing technique to organize folksonomy tags. Folksonomy tags
have no explicit relations and vary because they form uncontrolled vocabulary. We discriminates so-called subjective tagslike “cool” and “fun” from folksonomy tags without any extra knowledge other than folksonomy triples and use the level oftag generalization to form the objective tags into a hierarchy. We verify that entropy of folksonomy tags is an effectivemeasure for discriminating subjective folksonomy tags. Our hierarchical tag allocation method guarantees the number of childrennodes and increases the number of available paths to a target node compared to an existing tree allocation method for folksonomytags.
%0 Journal Article
%1 takeharu2009
%A Eda, T.
%A Yoshikawa, M.
%A Uchiyama, T.
%A Uchiyama, T.
%D 2009
%J World Wide Web
%K folksonomy goals motivation tagging taggingsurvey
%N 4
%P 421--440
%T The Effectiveness of Latent Semantic Analysis for Building Up a Bottom-up Taxonomy from Folksonomy Tags
%U http://dx.doi.org/10.1007/s11280-009-0069-1
%V 12
%X Abstract In this paper, we evaluate the effectiveness of a semantic smoothing technique to organize folksonomy tags. Folksonomy tags
have no explicit relations and vary because they form uncontrolled vocabulary. We discriminates so-called subjective tagslike “cool” and “fun” from folksonomy tags without any extra knowledge other than folksonomy triples and use the level oftag generalization to form the objective tags into a hierarchy. We verify that entropy of folksonomy tags is an effectivemeasure for discriminating subjective folksonomy tags. Our hierarchical tag allocation method guarantees the number of childrennodes and increases the number of available paths to a target node compared to an existing tree allocation method for folksonomytags.
@article{takeharu2009,
abstract = {Abstract In this paper, we evaluate the effectiveness of a semantic smoothing technique to organize folksonomy tags. Folksonomy tags
have no explicit relations and vary because they form uncontrolled vocabulary. We discriminates so-called subjective tagslike “cool” and “fun” from folksonomy tags without any extra knowledge other than folksonomy triples and use the level oftag generalization to form the objective tags into a hierarchy. We verify that entropy of folksonomy tags is an effectivemeasure for discriminating subjective folksonomy tags. Our hierarchical tag allocation method guarantees the number of childrennodes and increases the number of available paths to a target node compared to an existing tree allocation method for folksonomytags.},
added-at = {2009-10-30T09:21:58.000+0100},
author = {Eda, T. and Yoshikawa, M. and Uchiyama, T. and Uchiyama, T.},
biburl = {https://www.bibsonomy.org/bibtex/2da0c721d646af6a0d9703d0f6446357d/mstrohm},
interhash = {a560796c977bc7582017f662bf88c16d},
intrahash = {da0c721d646af6a0d9703d0f6446357d},
journal = {World Wide Web},
keywords = {folksonomy goals motivation tagging taggingsurvey},
month = {December},
number = 4,
pages = {421--440},
timestamp = {2012-01-25T17:01:02.000+0100},
title = {The Effectiveness of Latent Semantic Analysis for Building Up a Bottom-up Taxonomy from Folksonomy Tags},
url = {http://dx.doi.org/10.1007/s11280-009-0069-1},
volume = 12,
year = 2009
}