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A new heuristic method called Topology Mining (TM) is proposed for topology optimization of framed structures, where the problem is formulated as 0-1 mixed-integer optimization problem. TM uses the apriori algorithm, developed in the field of data mining, to efficiently extract the bar sets that frequently appears among superior solutions, and proceeds so as to preserve the sets. Hence, the process of optimization can be investigated by tracing the frequent bar sets, accordingly, the parameters for optimization can easily be adjusted. It is pointed out that the ground structure method based on nonlinear programming is not effective for finding optimal placement of braces for a given frame under local buckling constraints. We propose an integrated approach to obtain an accurate solution of this problem, where optimal placement of braces is searched by TM, and the sizing optimization is performed by nonlinear programming. Three numerical examples are solved to demonstrate the performance of TM in comparison with another heuristic method called tabu search.