In recent literature, several models were proposed for reproducing and understanding the tagging behavior of users. They all assume that the tagging behavior is influenced by the previous tag assignments of other users. But they are only partially successful in reproducing characteristic properties found in tag streams. We argue that this inadequacy of existing models results from their inability to include user's background knowledge into their model of tagging behavior. This paper presents a generative tagging model that integrates both components, the background knowledge and the influence of previous tag assignments. Our model successfully reproduces characteristic properties of tag streams. It even explains effects of the user interface on the tag stream.
%0 Conference Paper
%1 dellschaft2008epistemic
%A Dellschaft, Klaas
%A Staab, Steffen
%B Proceedings of the nineteenth ACM conference on Hypertext and hypermedia
%C New York, NY, USA
%D 2008
%I ACM
%K PhD models taggingsurvey
%P 71--80
%R 10.1145/1379092.1379109
%T An epistemic dynamic model for tagging systems
%U http://doi.acm.org/10.1145/1379092.1379109
%X In recent literature, several models were proposed for reproducing and understanding the tagging behavior of users. They all assume that the tagging behavior is influenced by the previous tag assignments of other users. But they are only partially successful in reproducing characteristic properties found in tag streams. We argue that this inadequacy of existing models results from their inability to include user's background knowledge into their model of tagging behavior. This paper presents a generative tagging model that integrates both components, the background knowledge and the influence of previous tag assignments. Our model successfully reproduces characteristic properties of tag streams. It even explains effects of the user interface on the tag stream.
%@ 978-1-59593-985-2
@inproceedings{dellschaft2008epistemic,
abstract = {In recent literature, several models were proposed for reproducing and understanding the tagging behavior of users. They all assume that the tagging behavior is influenced by the previous tag assignments of other users. But they are only partially successful in reproducing characteristic properties found in tag streams. We argue that this inadequacy of existing models results from their inability to include user's background knowledge into their model of tagging behavior. This paper presents a generative tagging model that integrates both components, the background knowledge and the influence of previous tag assignments. Our model successfully reproduces characteristic properties of tag streams. It even explains effects of the user interface on the tag stream.},
acmid = {1379109},
added-at = {2012-02-21T14:08:29.000+0100},
address = {New York, NY, USA},
author = {Dellschaft, Klaas and Staab, Steffen},
biburl = {https://www.bibsonomy.org/bibtex/27877bf1d91bd35067461c306b7f6fd00/chriskoerner},
booktitle = {Proceedings of the nineteenth ACM conference on Hypertext and hypermedia},
description = {An epistemic dynamic model for tagging systems},
doi = {10.1145/1379092.1379109},
interhash = {cc0d1d4f43effbb6eb7d463422e6c00b},
intrahash = {7877bf1d91bd35067461c306b7f6fd00},
isbn = {978-1-59593-985-2},
keywords = {PhD models taggingsurvey},
location = {Pittsburgh, PA, USA},
numpages = {10},
pages = {71--80},
publisher = {ACM},
series = {HT '08},
timestamp = {2012-04-15T16:45:51.000+0200},
title = {An epistemic dynamic model for tagging systems},
url = {http://doi.acm.org/10.1145/1379092.1379109},
year = 2008
}