An epistemic dynamic model for tagging systems Export

@inproceedings{citeulike:2948484, 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.}, address = {New York, NY, USA}, author = {Dellschaft, Klaas and Staab, Steffen}, booktitle = {HT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia}, citeulike-article-id = {2948484}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1379109}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1379092.1379109}, doi = {10.1145/1379092.1379109}, isbn = {978-1-59593-985-2}, keywords = {complex-systems, enterprise, stochastic-modeling, tagging, temporal-evolution}, location = {Pittsburgh, PA, USA}, pages = {71--80}, posted-at = {2008-10-20 08:53:42}, priority = {2}, publisher = {ACM}, title = {An epistemic dynamic model for tagging systems}, url = {http://dx.doi.org/10.1145/1379092.1379109}, year = {2008} }

TY - CONF ID - citeulike:2948484 L3 - citeulike-article-id:2948484 N2 - 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. CY - Pittsburgh, PA, USA SN - 978-1-59593-985-2 AD - New York, NY, USA EP - 80 TI - An epistemic dynamic model for tagging systems PB - ACM T2 - HT '08: Proceedings of the nineteenth ACM conference on Hypertext and hypermedia SP - 71 KW - complex-systems KW - enterprise KW - stochastic-modeling KW - tagging KW - temporal-evolution AU - Dellschaft, Klaas AU - Staab, Steffen PY - 2008/// UR - http://dx.doi.org/10.1145/1379092.1379109 ER -