A Portal-based Precision Advertising System Architecture Design

Online advertising is one of the Internet’s main profit models. It supports thedevelopment of the Internet industry. Compared to traditional advertising, mostadvertisers prefer to online advertising. Online advertising can be precision pushed tothe Internet users based on demographic and other factors. Meanwhile, the statisticaltools can measure the effect. Throughout the history of online advertising, how tomake full use of the remaining traffic and improve advertisers, media and users gainis currently the core issues to be addressed. As a demand-driven Internet product, thesystem architecture and algorithm selection is also diverse under different usagescenarios.To take full advantage of the remaining traffic this article designs a simple portalprecision advertising system. The system consists of five modules: Ad server, Sessionlog, Targeting, Ad index and Ad exchange. It supports three advertising push logicincluding Targeted Advertising, similar recommendations and Ad Exchange andcovered most of the core modules of accurate advertising system. To solve theproblem of qualitative ad retrieval and long-Query ad matching problem, the systemwill choose DNF and Weak AND as the core algorithm in Ad index. Meanwhile, thisarticle using the stream merge method improves the DNF algorithm. To better meetthe needs of diverse attributes of advertisers’ demand and the diverse attributes of usertab in index. Therefore, solving the advertising portal computing core issues that pushbest ads for different users on different pages and optimizing the overall input-outputratio.The DNF algorithm improvements are the greatest originality of this article.Using stream merge method, the improvements solve the "and" relationship ofmulti-value user tag attribute search and the "and" relationship of multi-valuedattribute indexing. Using the two parts improvements in the same system bringsconvenience to the Targeting Criteria.