Discovering shared conceptualizations in folksonomies

@unpublished{citeulike:2273576, abstract = {Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples. {\copyright} 2007 Elsevier B.V. All rights reserved. Article in Press}, address = {Institute for Algebra, Dresden University of Technology, 01062 Dresden, Germany 3}, author = {Ja?schke, R. and Hotho, A. and Schmitz, C. and Ganter, B. and Stumme, G. }, citeulike-article-id = {2273576}, doi = {http://dx.doi.org/10.1016/j.websem.2007.11.004}, journal = {Web Semant.}, keywords = {analytic, conceptual, conceptual\_analysis, cultural\_schemas, folksonomy, social\_network, tagging}, posted-at = {2008-04-27 18:46:54}, priority = {5}, title = {Discovering shared conceptualizations in folksonomies}, url = {http://dx.doi.org/10.1016/j.websem.2007.11.004} }

TY - INPR ID - citeulike:2273576 L3 - citeulike-article-id:2273576 TI - Discovering shared conceptualizations in folksonomies JF - Web Semant. AD - Institute for Algebra, Dresden University of Technology, 01062 Dresden, Germany 3 N2 - Social bookmarking tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. Unlike ontologies, shared conceptualizations are not formalized, but rather implicit. We present a new data mining task, the mining of all frequent tri-concepts, together with an efficient algorithm, for discovering these implicit shared conceptualizations. Our approach extends the data mining task of discovering all closed itemsets to three-dimensional data structures to allow for mining folksonomies. We provide a formal definition of the problem, and present an efficient algorithm for its solution. Finally, we show the applicability of our approach on three large real-world examples. © 2007 Elsevier B.V. All rights reserved. Article in Press KW - analytic KW - conceptual KW - conceptual_analysis KW - cultural_schemas KW - folksonomy KW - social_network KW - tagging AU - Ja?schke, R AU - Hotho, A AU - Schmitz, C AU - Ganter, B AU - Stumme, G UR - http://dx.doi.org/10.1016/j.websem.2007.11.004 ER -