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Table 1.

Reviews of the sentiment mining for different categorization schemes and techniques.

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Fig 1.

The proposed method.

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Fig 1 Expand

Table 2.

OHSUMED category descriptions.

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Table 2 Expand

Table 3.

Feature descriptions.

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Table 3 Expand

Table 4.

TF-IDF parameter descriptions.

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Table 5.

Description of PCA outputs.

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Table 6.

Classifier parameter settings.

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Table 7.

Confusion matrix for sentiment classification.

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Table 8.

Properties of the Movie and OHSUMED datasets.

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Table 9.

Experimental module (Movie dataset).

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Table 9 Expand

Fig 2.

The effect of additional attributes for different modules (Movie dataset).

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Fig 2 Expand

Table 10.

Comparison of results without dimension reduction (Movie dataset).

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Table 11.

Dimension reduction results (Movie dataset).

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Table 12.

Experimental module (Ohsumed dataset).

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Table 12 Expand

Fig 3.

The effect of additional attributes on the different modules (OHSUMED dataset).

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Fig 3 Expand

Table 13.

Results of the OHSUMED dataset without dimension reduction.

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Table 14.

Results of the OHSUMED dataset with dimension reduction.

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Table 15.

The total implementation time of five classifiers (time unit: Second).

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