Abstract: Embodiments of the present invention are directed to grouping clients in a work marketplace into clusters such that, in each cluster, clients are similar with respect to their hiring criteria. In some embodiments, the clusters are generated based on a clustering algorithm that can be applied effectively on large datasets. This separation allows the work marketplace to discover differences in client hiring criteria, to learn more accurately the hiring criteria in each cluster and to recommend the right contractor to each client for a successful collaboration, thereby improving matching between clients and contractors in the work marketplace. For each contractor who have submitted an application to a project posted by a client, a contractor/opening pair score is determined based on information of the cluster that is associated with the client. The contractor/opening pair score is used to ascertain whether the contractor would be a candidate recommended to the client.

Abstract: A computer-based system for automatic pagination and layout of yellow pages or a commercial telephone directory uses a simulated annealing heuristic to refine a randomly determined candidate solution. The text and advertisements which are to be included in the yellow pages directory are ordered in two distinct data streams representing the order of text and the order of advertisements in the directory. The system determines a possible layout, called a candidate solution, by randomly setting parameters defining the pagination and layout. These parameters may include page breaks in the advertisement stream, column numbers for each advertisement, and an amount of padding or empty space to be added to each page. Once the parameters are set, the individual pages are laid out by putting the advertisements in the next available position in their assigned columns, and the text around the advertisements. The solution is scored based upon the guidelines for the format and layout of the yellow pages directory.