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Semi-supervised learning is drawing increasing attention in the era of big data, as the gap between the abundance of cheap, automatically collected unlabeled data and the scarcity of labeled data that are laborious and expensive to obtain is dramatically increasing. In this paper, we first introduce a unified view of density-based clustering algorithms. We then build upon this view and bridge the areas of semi-supervised clustering and classification under a common umbrella of density-baseddoi:10.1007/s10618-019-00651-1 pmid:32831623 pmcid:PMC7410108 fatcat:z6gl6cnj3zhb3fupcu3grnhk7a