Constructing Folksonomies from User-specified Relations on Flickr
Anon Plangprasopchok, Kristina Lerman

TL;DR
This paper presents a method to build folksonomies by aggregating hierarchical relations from Flickr users, using statistical techniques to filter and combine individual user-created hierarchies into a collective classification system.
Contribution
It introduces a simple, statistically-driven approach to aggregate user-defined hierarchical relations into a coherent folksonomy, leveraging social annotations.
Findings
Generated reasonable, non-trivial hierarchies
Approach appears promising despite lack of detailed quantitative evaluation
Utilizes collective user annotations to infer concept relationships
Abstract
Many social Web sites allow users to publish content and annotate with descriptive metadata. In addition to flat tags, some social Web sites have recently began to allow users to organize their content and metadata hierarchically. The social photosharing site Flickr, for example, allows users to group related photos in sets, and related sets in collections. The social bookmarking site Del.icio.us similarly lets users group related tags into bundles. Although the sites themselves don't impose any constraints on how these hierarchies are used, individuals generally use them to capture relationships between concepts, most commonly the broader/narrower relations. Collective annotation of content with hierarchical relations may lead to an emergent classification system, called a folksonomy. While some researchers have explored using tags as evidence for learning folksonomies, we believe that…
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Taxonomy
TopicsTopic Modeling · Text and Document Classification Technologies · Biomedical Text Mining and Ontologies
