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Determining valuable data among large volumes of data is one of the main challenges in Big Data. We aim to extract knowledge from these sources using a Hierarchical Multi-Label Classification process called Semantic HMC. This process automatically learns a label hierarchy and classifies items from very large data sources. Five steps compose the Semantic HMC process: Indexation, Vectorization, Hierarchization, Resolution and Realization. The first three steps construct automatically the labeldoi:10.1145/2928294.2928301 dblp:conf/sigmod/PeixotoHCBS16 fatcat:f6ina2i74rfmrpzk76z45wmrnu