RMIT and University of Melbourne researchers teamed up with SEEK in an Australian Research Council Linkage project to apply their search engine and user analytics expertise to SEEK’s job-search system. Project Lead, RMIT's Associate Professor Lawrence Cavedon, said the Seeksy query amendment system they had developed used text mining techniques, informed by analysis of user history and behaviours, to expand search terms in relevant ways for each query. Seeksy implements the ability to cope with synonyms like “governess” and “nanny”, or to modify overly specific queries like “training train driver” into “train driver” to increase job matches. Comparative A/B testing of the technique conducted by SEEK showed click-through rates increased four-fold, and actual job applications six-fold, for certain common queries that had proven hard to find relevant results for. Cavedon said it was satisfying to know that the improvements had been based on evidence of actual user needs.