Elias Oliveira,  Patrick Marques Ciarelli,  Felipe Pedroni,  Wallace Favoreto Henrique,  Lucas Veronese. 

Automatic text classification is still a challenging in the literature, specially for multi-label classification. In this work we evaluate the performance of the Multi-Label k-Nearest Neighbor algorithm for a multi-labeled dataset with more than 1,000 possible labels to be assigned to each one of the documents in the dataset. The results are promising.

http://www.lbd.dcc.ufmg.br/colecoes/til/2008/0021.pdf

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