Design of Online Advertising Precise Marketing System Based on Collaborative Filtering Algorithm

During the rapid development of communication technology, network technology and computer application technology, my country has entered a new era of big data. The traditional mode of data information dissemination has undergone earth-shaking changes, which can make online media advertising more accurate, more diverse, and more personalized. With the increasingly fierce media competition, the more and more difficult to grasp the needs of the audience, and the higher and higher requirements of advertisers for advertising effects, it is difficult for traditional advertising to accurately capture the actual needs of consumers, and it cannot meet the needs of enterprises. “Precision” has gradually become the goal pursued by the advertising industry. The emergence of new media provides more carriers for precise advertising, such as mobile phone-based mobile advertising, network-based narrow advertising, point advertising, and talk advertising. This paper uses the collaborative filtering algorithm. The recommendation effect of the improved user-based collaborative filtering algorithm is better than that of the traditional algorithm. This technology adopts statistical thinking, analyzes the relationship between users and users and items and items by mining a large amount of historical information, and actively provides the target users with the resources they need.