This paper describes a Web search optimization study that investigates both static and dynamic tuning methods for optimizing system performance. We extended the conventional fusion approach by introducing the “dynamic tuning” process with which to optimize the fusion formula that combines the contributions of diverse sources of evidence on the Web. By engaging in iterative dynamic tuning process, where we successively fine-tuned the fusion parameters based on the cognitive analysis of immediate system feedback, we were able to significantly increase the retrieval performance.Our results show that exploiting the richness of Web search environment by combining multiple sources of evidence is an effective strategy.