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Extractive Summarization using Continuous Vector Space Models

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Figure

Figure 3: The figure shows an auto-encoder thatcompresses four dimensional data into a two di-mensional code
Figure 4: The recursive neural network architec-ture makes it possible to handle variable length in-put data
Figure 6: The structure of an unfolding RAE, ona three word phrase (tations, whiletrix[ x 1 , x 2 , x 3 ] )
Table 1: ROUGE scores for summaries using dif-ferent similarity measures.OPT constitutes theoptimal ROUGE scores on this dataset.

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