当前,随着互联网用户的持续增长,广告行业面临前所未有的挑战,如何将广告传递给目标受众成为当今研究的热点。数据挖掘为个性化推荐提供了理论支撑,RTB的出现也将广告主纳入推荐的流程中,然而,现存RTB尚不能准确定位用户的意图,本文提出应用web关键字挖掘、协同过滤算法和关联推荐相结合的方法完成广告项目的推荐,集过去、现在和将来三个时段,提出了用户兴趣度和活跃度指标,补充了推荐产生的影响因素。 At present, with the continuous growth of Internet users, the advertising industry is facing unprecedented challenges. How to deliver advertisements to the target audience has become a hot spot in today’s research. However, the existing RTB can not accurately locate the user’s intention. This paper proposes the application of web keyword mining, collaborative filtering algorithm and related recommendation A combination of methods to complete the recommendation of advertising projects, set the past, present and future three periods, put forward the user interest and activity index to supplement the recommendations of the impact of factors.