We consider the problem of designing truthful auctions, when the bidders'
valuations have a public and a private component. In particular, we consider
combinatorial auctions where the valuation of an agent i for a set S of
items can be expressed as vif(S), where vi is a private single parameter
of the agent, and the function f is publicly known. Our motivation behind
studying this problem is two-fold: (a) Such valuation functions arise naturally
in the case of ad-slots in broadcast media such as Television and Radio. For an
ad shown in a set S of ad-slots, f(S) is, say, the number of {\em unique}
viewers reached by the ad, and vi is the valuation per-unique-viewer. (b)
From a theoretical point of view, this factorization of the valuation function
simplifies the bidding language, and renders the combinatorial auction more
amenable to better approximation factors. We present a general technique, based
on maximal-in-range mechanisms, that converts any α-approximation
non-truthful algorithm (α≤1) for this problem into
Ω(lognα) and Ω(α)-approximate truthful
mechanisms which run in polynomial time and quasi-polynomial time,
respectively