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Abstract:
Online communities have recently become a popular tool for publishing and
searching content, as well as for finding and connecting to other users that
share common interests. The content is typically user-generated and includes,
for example, personal blogs, bookmarks, and digital photos. A particularly
intriguing type of content is user-generated annotations (tags) for content
items, as these concise string descriptions allow for reasonings about the
interests of the user who created the content, but also about the user who
generated the annotations. This paper presents a framework to cast the
different entities of such networks into a unified graph model representing the
mutual relationships of users, content, and tags. It derives scoring functions
for each of the entities and relations. We have performed an experimental
evaluation on two real-world datasets (crawled from deli.cio.us and Flickr)
where manual user assessments of the query result quality show that our unified
graph framework delivers high-quality results on social networks.
