Online recruitment services suffer from shortcomings due to traditional search techniques. Most users fail to construct queries
that provide an adequate and accurate description of their (job) requirements, leading to imprecise search results. We investigate
one potential solution that combines implicit profiling methods and automated collaborative filtering (ACF) techniques to
build personalised query-less job recommendations. Two ACF strategies are implemented and evaluated in the JobFinder domain.