  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 $v_if(S)$, where $v_i$ 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 $v_i$ 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 $\alpha$-approximation
non-truthful algorithm ($\alpha \leq 1$) for this problem into
$\Omega(\frac{\alpha}{\log{n}})$ and $\Omega(\alpha)$-approximate truthful
mechanisms which run in polynomial time and quasi-polynomial time,
respectively.
