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2007
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An unsupervised hierarchical approach to document categorization

9 years 6 months ago
An unsupervised hierarchical approach to document categorization
— We propose a hierarchical approach to document categorization that requires no pre-configuration and maps the semantic document space to a predefined taxonomy. The utilization of search engines to train a hierarchical classifier makes our approach more flexible than existing solutions which rely on (human) labeled data and are bound to a specific domain. We show that the structural information given by the taxonomy allows for a context aware construction of search queries and leads to higher tagging accuracy. We test our approach on different benchmark datasets and evaluate its performance on the single- and multi-tag assignment tasks. The experimental results show that our solution is as accurate as supervised classifiers for web page classification and still performs well when categorizing domain specific documents.
Robert Wetzker, Tansu Alpcan, Christian Bauckhage,
Added 09 Jun 2010
Updated 09 Jun 2010
Type Conference
Year 2007
Where WEBI
Authors Robert Wetzker, Tansu Alpcan, Christian Bauckhage, Winfried Umbrath, Sahin Albayrak
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