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Then, data is trained by using a partial back\u2010propagation neural network. The learning is guided by users' click behaviors.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Findings<\/jats:title><jats:p>Experimental results have shown the effectiveness of the approach.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-heading\">Originality\/value<\/jats:title><jats:p>The approach attempts to integrate metric of interests (e.g., click behavior, ranking) into the strategy of the recommendation system. Relevant results are first presented on the basis of a novel data structure named FPT\u2010tree, and then, those results are trained through a partial back\u2010propagation neural network. 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