Optimization Issues in Web and Mobile Advertising
Author | : Subodha Kumar |
Publisher | : Springer |
Total Pages | : 76 |
Release | : 2015-11-13 |
ISBN-10 | : 9783319186450 |
ISBN-13 | : 3319186450 |
Rating | : 4/5 (50 Downloads) |
Download or read book Optimization Issues in Web and Mobile Advertising written by Subodha Kumar and published by Springer. This book was released on 2015-11-13 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of optimization issues and models in web and mobile advertising. It begins by discussing the evolution of web advertising over time. This is followed by the discussion of prominent pricing models. The reader is provided with a basic overview of different optimization issues involved in web advertising. The earlier models mainly considered the problem of scheduling ads competing to be placed on a web page. Here, the ads were specified by geometry and display frequency, and both of these factors were considered in developing a solution to the advertisement scheduling problem. These models were similar in nature to the problem of scheduling ads on newspaper or television, but the pricing structure in these models were different from those in newspaper or television ads. As the web advertising evolved, the initial models were augmented by considering how the schedule of ads is changed based on individual user click behavior. Thus, these models considered personalization in web advertising. The book also presents methods to help solve these models. More recently, there has been tremendous growth in mobile advertising. This book also provides the details of business model in mobile advertising, and presents solutions for the optimization problem involved in mobile advertising. Additionally this book looks to key future trends in web and mobile advertising (such as Fading Ads) and the associat ed challenges that come with it. For instance, the future trends in pricing models are more towards action-based pricing rather than impression-based pricing.