  Domain name registrars and URL shortener service providers place
advertisements on the parked domains (Internet domain names which are not in
service) in order to generate profits. As the web contents have been removed,
it is critical to make sure the displayed ads are directly related to the
intents of the visitors who have been directed to the parked domains. Because
of the missing contents in these domains, it is non-trivial to generate the
keywords to describe the previous contents and therefore the users intents. In
this paper we discuss the adaptive keywords extraction problem and introduce an
algorithm based on the BM25F term weighting and linear multi-armed bandits. We
built a prototype over a production domain registration system and evaluated it
using crowdsourcing in multiple iterations. The prototype is compared with
other popular methods and is shown to be more effective.
