Some auction mechanisms can be shown to be efficient and strategy-proof. However, they generally require that the preferences of at least one side of the auction are publicly known. However, sometimes it is very costly, impossible, or undesirable to publicly announce such preferences. It thus is interesting to find methods that do not impose this constraint but still approximate the outcome of the auction. In this paper we show that a multi-round multi-party negotiation protocol may be used to this end if the negotiating agents are capable of learning opponent preferences. The latter condition can be met by current state of the art negotiation technology. We show that this protocol approximates the theoretical outcome predicted by a so-called Qualitative Vickrey auction mechanism (even) on a complex multi-issue domain.