Fig. 2 The results of PCA, “n” stands for news text, “s” for science text, “o” for official text, “a” for artistic text, “t” for tv conversation text,

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Presentation transcript:

Fig. 2 The results of PCA, “n” stands for news text, “s” for science text, “o” for official text, “a” for artistic text, “t” for tv conversation text, “d” for daily conversation text From: Analysis on Chinese quantitative stylistic features based on text mining Lit Linguist Computing. 2014;31(2):357-367. doi:10.1093/llc/fqu067 Lit Linguist Computing | Digital Scholarship in the Humanities © The Author 2014. Published by Oxford University Press on behalf of EADH. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Fig. 1 The results of PCA, “dh” stands for daily conversation text, “qq” for tv conversation text, “art” for artistic text, “sc” for scientific text, “new” for news text, “official” for official text From: Analysis on Chinese quantitative stylistic features based on text mining Lit Linguist Computing. 2014;31(2):357-367. doi:10.1093/llc/fqu067 Lit Linguist Computing | Digital Scholarship in the Humanities © The Author 2014. Published by Oxford University Press on behalf of EADH. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Fig. 3 The dendrogram of hierarchical clustering From: Analysis on Chinese quantitative stylistic features based on text mining Lit Linguist Computing. 2014;31(2):357-367. doi:10.1093/llc/fqu067 Lit Linguist Computing | Digital Scholarship in the Humanities © The Author 2014. Published by Oxford University Press on behalf of EADH. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Fig. 4 Importance of POS (expressed in MeanDecreaseAccuracy and MeanDecreaseGini) From: Analysis on Chinese quantitative stylistic features based on text mining Lit Linguist Computing. 2014;31(2):357-367. doi:10.1093/llc/fqu067 Lit Linguist Computing | Digital Scholarship in the Humanities © The Author 2014. Published by Oxford University Press on behalf of EADH. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Fig. 5 The weighted entropy of hierarchical clustering of texts represented by different POS From: Analysis on Chinese quantitative stylistic features based on text mining Lit Linguist Computing. 2014;31(2):357-367. doi:10.1093/llc/fqu067 Lit Linguist Computing | Digital Scholarship in the Humanities © The Author 2014. Published by Oxford University Press on behalf of EADH. All rights reserved. For Permissions, please email: journals.permissions@oup.com