  Recruitment in large organisations often involves interviewing a large number
of candidates. The process is resource intensive and complex. Therefore, it is
important to carry it out efficiently and effectively. Planning the selection
process consists of several problems, each of which maps to one or the other
well-known computing problem. Research that looks at each of these problems in
isolation is rich and mature. However, research that takes an integrated view
of the problem is not common. In this paper, we take two of the most important
aspects of the application processing problem, namely review/interview panel
creation and interview scheduling. We have implemented our approach as a
prototype system and have used it to automatically plan the interview process
of a real-life data set. Our system provides a distinctly better plan than the
existing practice, which is predominantly manual. We have explored various
algorithmic options and have customised them to solve these panel creation and
interview scheduling problems. We have evaluated these design options
experimentally on a real data set and have presented our observations. Our
prototype and experimental process and results may be a very good starting
point for a full-fledged development project for automating application
processing process.
