Cha, M.; Kwak, H.; Rodriguez, P.; Ahn, Y. & Moon, S.
(2007):
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system.
Erscheinungsjahr/Year: 2007.
Seiten/Pages: 1-14.
[BibTeX]
[Endnote]
@article{cha2007tyt,
author = {Cha, M. and Kwak, H. and Rodriguez, P. and Ahn, Y.Y. and Moon, S.},
title = {I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system},
booktitle = {Proceedings of the 7th ACM SIGCOMM conference on Internet measurement},
year = {2007},
pages = {1--14},
keywords = {sna, web2.0, youtube}
}
%0 = article
%A = Cha, M. and Kwak, H. and Rodriguez, P. and Ahn, Y.Y. and Moon, S.
%B = Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
%D = 2007
%T = I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
'tag based clustering may not be adapted for this kind of distribution [power law]':
Hayes, C. & Avesani, P.
(2007):
Using Blog Tags To Identify Topic Authorities.
[Volltext] [Kurzfassung] [BibTeX]
[Endnote]
The Web has experienced an exponential growth in the use of weblogs or blogs. Blog entries are generally organised using tags, informally defined labels which are increasingly being proposed as a 'grassroots' answer to Semantic Web standards. Despite this, tags have been shown to be weak at partitioning blog data. In this paper, we demonstrate how tags provide useful, discriminating information where the blog corpus is initially partitioned using a conventional clustering technique. Using extensive empirical evaluation we demonstrate how tag cloud information within each cluster allows us to identify potentially strong topic 'authorities' in each cluster. We conclude that tags have a key auxiliary role in refining and confirming the information produced using typical knowledge discovery techniques.
@unpublished{hayes:ubt,
author = {Hayes, C. and Avesani, P.},
title = {Using Blog Tags To Identify Topic Authorities},
year = {2007},
note = {'tag based clustering may not be adapted for this kind of distribution [power law]'},
url = {https://apps.lis.uiuc.edu/wiki/display/LEADS/Fall+2007+Archive},
keywords = {folksonomy, law, power, tagging, web2.0},
abstract = {The Web has experienced an exponential growth in the use of weblogs or blogs. Blog entries are generally organised using tags, informally defined labels which are increasingly being proposed as a 'grassroots' answer to Semantic Web standards. Despite this, tags have been shown to be weak at partitioning blog data. In this paper, we demonstrate how tags provide useful, discriminating information where the blog corpus is initially partitioned using a conventional clustering technique. Using extensive empirical evaluation we demonstrate how tag cloud information within each cluster allows us to identify potentially strong topic 'authorities' in each cluster. We conclude that tags have a key auxiliary role in refining and confirming the information produced using typical knowledge discovery techniques.}
}
%0 = unpublished
%A = Hayes, C. and Avesani, P.
%D = 2007
%T = Using Blog Tags To Identify Topic Authorities
%U = https://apps.lis.uiuc.edu/wiki/display/LEADS/Fall+2007+Archive
Hayes, C.; Avesani, P. & Veeramachaneni, S.
(2006):
An analysis of the use of tags in a blog recommender system.
In: ITC-IRST Technical Report. http://sra. itc. it/people/hayes/pubs/06/hayes-ijcai07-tech-report. pdf,
Erscheinungsjahr/Year: 2006.
[BibTeX]
[Endnote]
@article{hayes2006aut,
author = {Hayes, C. and Avesani, P. and Veeramachaneni, S.},
title = {An analysis of the use of tags in a blog recommender system},
journal = {ITC-IRST Technical Report. http://sra. itc. it/people/hayes/pubs/06/hayes-ijcai07-tech-report. pdf},
year = {2006},
keywords = {folksonomy, tagging, web2.0}
}
%0 = article
%A = Hayes, C. and Avesani, P. and Veeramachaneni, S.
%D = 2006
%T = An analysis of the use of tags in a blog recommender system