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The problem of closed frequent itemset discovery is a fundamental problem of data mining, having applications in numerous domains. It is thus very important to have efficient parallel algorithms to solve this probem, capable of efficiently harnessing the power of multicore processors that exists in our computers (notebooks as well as desktops). In this paper we present PLCMQS, a parallel algorithm based on the LCM algorithm, recognized as the most efficient algorithm for sequential discovery ofdoi:10.1109/hpcs.2010.5547082 dblp:conf/ieeehpcs/NegrevergneTMU10 fatcat:yh2lmtcrhzetbhk5p5e6xmh544