Turning down the noise in the blogosphere

In recent years, the blogosphere has experienced a substantial increase in the number of posts published daily, forcing users to cope with information overload. The task of guiding users through this flood of information has thus become critical. To address this issue, we present a principled approach for picking a set of posts that best covers the important stories in the blogosphere. We define a simple and elegant notion of coverage and formalize it as a submodular optimization problem, for which we can efficiently compute a near-optimal solution. In addition, since people have varied interests, the ideal coverage algorithm should incorporate user preferences in order to tailor the selected posts to individual tastes. We define the problem of learning a personalized coverage function by providing an appropriate user-interaction model and formalizing an online learning framework for this task. We then provide a no-regret algorithm which can quickly learn a user's preferences fro...

• Type: Conference
• Year: 2009
• Where: KDD
• Authors: Khalid El-Arini, Gaurav Veda, Dafna Shahaf, Carlos Guestrin
• Keywords: Data Mining, Ideal Coverage Algorithm, KDD 2009, Simple Coverage Algorithm, User Preferences