Targeted advertising optimization using vector space model for online behavior on news portal computational advertising case study: Harianjogja.com

Targeted advertising is the placement of advertising in order to reach much attraction as many users. The raise of targeted advertising can be gain by using an optimization on demography, geography, and online behavior. While online advertising behavior is that gather information about the online activities of web users (such as visited web user) and use it to display relevant ads or content to the web user habits. Everyday, thousands of users online treated by many kinds of advertisement, but not all of them were eye-catching. This phenomenon is playing an important role related to the interest of web users who will click on the advertisement. The development of computational advertising in Indonesia grew fastly, especially in news portal online. However, there were still many problems such as the sameness display ads on all topic in some news topic and the irrelevance between the advertisement with the news topic (for example: the stationary advertisement on the sport news). Consequently, the advertisement can not attract the attention of web users because it does not fit with the habits and intentions of visitors. So, it is necessary to optimize the system of advertisement showing in order to attract more web users who will visit the advertisement. This research will focus on optimizing behavior targeted online advertising that aims at adjusting display ads with habits of web users.