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We use K Nearest Neighbors (KNN) classic classification model and the Best Match (BM)25 probabilistic information retrieval model to assess how efficiently the classic KNN model could be modified to solve the real-life product categorizing problem. This paper gives a system description of the KNN-based algorithm for solving the product classification problem. Our submissions experimented are based on the Rakuten 1M product listings datasets in tsv format provided by the Rakuten Institute ofdblp:conf/sigir/HuZWFTH18 fatcat:3sttcxunq5g5neme6y6dxas4mq