Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/97003
Title: Evolutionary taxonomy construction from dynamic tag space
Authors: Yao, Junjie
Cui, Bin
Cong, Gao
Huang, Yuxin
Keywords: DRNTU::Engineering::Computer science and engineering
Issue Date: 2011
Source: Yao, J., Cui, B., Cong, G., & Huang, Y. (2012). Evolutionary taxonomy construction from dynamic tag space. World Wide Web, 15(5-6), 581-602.
Series/Report no.: World wide web
Abstract: Collaborative tagging becomes a common feature of current web sites, facilitating ordinary users to annotate and represent online resources. The large collection of tags and their relationships form a tag space. In this kind of tag space, the popularity and correlation amongst tags capture the current social interests. Tags are freely chosen keywords and difficult to organize. As a hierarchical concept structure to represent the subsumption relationships, automatically extracted taxonomies become a viable method to manage collaborative tags. However, tags change over time, and it is also imperative to incorporate the temporal tag evolution into the extracted taxonomies. In this paper, we formalize the problem of evolutionary taxonomy generation over a large collection of tags. A line of taxonomies are generated to reflect the temporal changes of underlying tag space. The proposed evolutionary taxonomy framework consists of two novel contributions. First, we develop a context-aware edge selection algorithm for taxonomy extraction. This method is built on seminal association-rule mining algorithm. Second, we propose several strategies for evolutionary taxonomy fusion, which smooths the newly generated taxonomy with prior ones. We conduct an extensive performance study using a large real-life web page tagging dataset (i.e., Del.ici.ous). The empirical results clearly verify the effectiveness and efficiency of the proposed approach.
URI: https://hdl.handle.net/10356/97003
http://hdl.handle.net/10220/11688
ISSN: 1386-145X
DOI: http://dx.doi.org/10.1007/s11280-011-0150-4
Rights: © 2011 Springer Science+Business Media, LLC.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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