Revenue-Optimized Webpage Recommendation

As a massive industry, display advertising delivers advertisers´ marketing messages to attract customers throughbanners shown on webpages. For publishers, i.e. websites, display advertising is the most critical revenue source. Most existing webpage recommender systems suggest webpages based on user interests only. However, the articles of interest to specific users may not be profitable to publishers. Conversely, only recommending the most profitable articles may lose publishers´ user base. To address this issue, we will conduct a series of investigations and design Revenue-Optimized Recommendation, aims to recommend users webpages that optimize interestingness and ad revenue.