Abstract
After the emergence of internet, online advertising has evolved as a major form of advertising in this century. The most important types of online advertising are sponsored search, contextual advertising and banner advertising. Banner advertising or display advertising is one of the predominant modes of online advertising. In this thesis, we present the approaches to improve the performance of display advertising.
The three important stakeholders in display advertising are advertiser, publisher and user. The publisher manages the ad space of the website(s) and several advertisers demand ad slots for advertisements. The advertiser aims to reach/spread the ad to the maximum number of targeted users of the website whereas the publisher aims to maximize the revenue by satisfying the demands of increased number of advertisers. The users visit web pages and the corresponding ads. The major issues involved in display advertising scenario are developing efficient approaches (i) for the publisher to meet the demands of the maximum number of advertisers, (ii) to schedule the ads to ad slots of web pages (iii) for auctioning and charging of ad slots (iv) for targeting ads and (v) for managing guaranteed and non-guaranteed contracts. In this thesis, we have made efforts to develop efficient ad allocation approaches for the publisher and a scalable management framework for display ad space management.
Firstly, 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 clickstream transactions. We explore the factors in adapting the knowledge of coverage patterns to benefit display advertising. Using the knowledge of coverage patterns extracted from a website clickstream transactional database, we identify supply of expected user visits to available ad slots of the website. Coverage patterns extracted from website clickstream transactional database contains a set of distinct web pages with corresponding coverage or percentage of users. With this information, we develop an efficient ad slots allocation approach which helps the publisher in selecting appropriate sets of web pages that satisfy coverage demands of advertisers and at the same time reduces repeated display of ads to users of the website. 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 clickstream 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.
Secondly, we propose a framework to harvest the pages views of the web. It can be observed that online advertising provides an opportunity for product sellers and service providers to reach customers and has become a key factor in the growth of economy. It is a major source of revenue most importantly for the search engine and social networking sites. Currently, the number of websites registered comes to a billion. Each day, a typical website receives the number of visitors ranging from hundreds to millions. In a few years, the relative association of users with internet as well as the number of websites will grow exponentially. In this context, it is possible for a product seller or service provider to reach every potential customer through display advertising. We propose that rather than managing a single website, the publisher manages the aggregated advertising space of a collection of websites. In this framework, websites can be divided into clusters based on the topic (or any other interesting measure) and the interested publishers can manage the aggregated advertisement space of the cluster. The proposed framework can provide wider opportunity for the publishers to play an active role in connecting the sellers with potential buyers. As a result, the advertisement space could be expanded significantly and it will provide the opportunity for increased number of publishers to market the aggregated advertisement space of millions of websites in an organized way. It will also help in balancing the management of banner advertising market in a transparent and controlled way.
Overall, in this thesis we have shown that the knowledge of coverage patterns extracted through clickstream transactions of the websites helps in efficient allocation of available display ad space to advertisers. In addition, we have proposed a scalable plan to exploit the banner advertisement space of the entire web. We hope that the proposed approaches enthuse the ad management companies to adopt and enable sellers to connect with