Optimizing web traffic via the media scheduling problem

Website traffic varies through time in consistent and predictable ways, with highest traffic in the middle of the day. When providing media content to visitors, it is important to present repeat visitors with new content so that they keep coming back. In this paper we present an algorithm to balance the need to keep a website fresh with new content with the desire to present the best content to the most visitors at times of peak traffic. We formulate this as the media scheduling problem, where we attempt to maximize total clicks, given the overall traffic pattern and the time varying clickthrough rates of available media content. We present an efficient algorithm to perform this scheduling under certain conditions and apply this algorithm to real data obtained from server logs, showing evidence of significant improvements in traffic from our algorithmic schedules. Finally, we analyze the click data, presenting models for why and how the clickthrough rate for new content declines as it...

• Type: Conference
• Year: 2009
• Where: KDD
• Authors: Lars Backstrom, Jon M. Kleinberg, Ravi Kumar
• Keywords: Available Media Content, Data Mining, KDD 2009, Media Scheduling Problem, Overall Traffic Pattern