Constructing folksonomies by integrating structured metadata

TitleConstructing folksonomies by integrating structured metadata
Publication TypeConference Papers
Year of Publication2010
AuthorsPlangprasopchok A, Lerman K, Getoor L
Conference NameProceedings of the 19th international conference on World wide web
Date Published2010///
Conference LocationNew York, NY, USA
ISBN Number978-1-60558-799-8
Keywordscollective knowledge, data mining, folksonomies

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.