document: Constructing folksonomies by integrating structured metadata Aggregating many personal hierarchies into a common taxonomy , also known as a folksonomy , presents several challenges due to its sparseness , ambiguity , noise , and inconsistency . We describe an approach to folksonomy learning based on relational clustering that addresses these challenges by exploiting structured metadata contained in personal hierarchies . Our approach clusters similar hierarchies using their structure and tag statistics , then incrementally weaves them into a deeper , bushier tree . We study folksonomy learning using social metadata extracted from the photo-sharing site Flickr . We evaluate the learned folksonomy quantitatively by automatically comparing it to a reference taxonomy created by the Open Directory Project . Our empirical results suggest that the proposed approach improves upon the state-of-the-art folksonomy learning method .
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