Coverage Patterns-Based Approach to Allocate Advertisement Slots for Display Advertising

Display advertising is one of the predominant modes of online advertising. A publisher makes efforts to allocate the available ad slots/page views to meet the demands of the maximum number of advertisers for maximizing the revenue. Investigating efficient approaches for ad slot allocation to advertisers is a research issue. In the literature, efforts are being made to propose approaches by extending optimization techniques. In this paper, we propose an improved approach for ad slot allocation by exploiting the notion of coverage patterns. In the literature, an approach is proposed to extract the knowledge of coverage patterns from the transactional databases. In the display advertising scenario, we propose an efficient ad slot allocation approach by exploiting the knowledge of coverage patterns extracted from the click stream transactions. The proposed allocation framework, in addition to the step of extraction of coverage patterns, contains mapping, ranking and allocation steps. The experimental results on both synthetic and real world click stream datasets show that the proposed approach could meet the demands of increased number of advertisers and reduces the boredom faced by user by reducing the repeated display of advertisements.