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Due to the limited labeled data, clustering is a solution for classifying documents that do not have prior knowledge. The combination of Latent Dirichlet Allocation (LDA) in grouping documents by topic and Term Frequency-Inverse Cluster Frequency (TFxICF) in the labeling was proposed to resolve the problem of classification using clustering completed with a description of the cluster results. Indonesian...
Text classification is a useful task in text mining. Most researchers employ one word weight type in the text classification. Here, we proposed to build a keyword list by combining several word weights for a rule based multi label text classification. Through this research, we conducted experiments on the term distribution clustering to produce the best automatic generated keyword list. We compared...
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