The so-called Social Web has helped to change the very nature of the Internet by emphasising the role of our online experiences as new forms of content and service knowledge. In this paper we describe an approach to improving main-stream Web search by harnessing the search experiences of groups of like-minded searchers. We focus on the HeyStaks system (www.heystaks.com) and look in particular at the experiential knowledge that drives its search recommendations. Specifically we describe how this knowledge can be noisy, and we describe and evaluate a recommendation technique for coping with this noise and discuss how it may be incorporated into HeyStaks as a useful feature.
