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ARABIC TEXT CLUSTERING BASED ON K MEANS ALGORITHM WITH SEMANTIC WORD EMBEDDING

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Figure

Table 1: Summarization of Recently published Researches on Arabic Document Clustering
Figure 1: CBOW and Skip-gram models architecture (taken from [32]).
Figure 2: Main approaches in Paragraph embedding model: (a) document vectors distributed memory model (PV-DM); (b) Paragraph Vector distributed Bag of words (PV-DBOW)
Figure 3: Proposed Framework for Arabic Document Clustering.
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