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Latent finger print matching is one of the freshest areas in science. The current methods of latent finger print matching are manual and reliable on human experience. Unfortunately, a system, which can perform the latent fingerprint matching automatically, does not exist. The eye tracking technology is able to record the eye movement and could provide useful information about the user search strategy. In this paper, the experimental data obtained from an eye tracker is analyzed by clustering analysis and a neural network based system is designed to learn the search strategy of the experts. The results show that the system is able to predict the optimum search strategy based on expert's experiences.