Partitioning and Ranking Tagged Data Sources
Online types of expression in the form of social networks, micro-blogging, blogs and rich content sharing platforms have proliferated in the last few years. Such proliferation contributed to the vast explosion in online data sharing the authors are experiencing today. One unique aspect of online data sharing is tags manually inserted by content generators to facilitate content description and discovery (e.g., hashtags in tweets). In this paper, they focus on these tags and they study and propose algorithms that make use of tags in order to automatically organize and categorize this vast collection of socially contributed and tagged information. In particular, they take a holistic approach in organizing such tags and they propose algorithms to partition as well as rank this information collection.