Research Article

Deep Learning Structure for Cross-Domain Sentiment Classification Based on Improved Cross Entropy and Weight

Table 11

Analysis of output results of W-RNN model.

(1) The layout of this book is very poor, and four or five pages in front are blank.
[(7, “poor”, 0.36663848), (17, “blank”, 0.16964875), (13, ”pages”, 0.16570723), (6, “very”, 0.11767213), (4, “book”, 0.07908833), (5, “is”, 0.0750145), (4, “this”, 0.06969571), (0, “the”, 0.04458785), (16,”front”, 0.023623824), (16, “are”, 0.006633401), (10, “four”, −0.0), (12, “five”, −0.015168488), (2, “of”, −0.022220552), (1, “layout”, −0.08092123)]

(2) This picture book is very good, my son likes it and has been reluctant to return it.
[(1, “picture”, 0.30500817), (5, “good”, 0.2046071), (4, “very”, 0.17955697), (2, “book”, 0.17825627), (4, ' 9′, 0.16365236), (14, “reluctant”, 0.15772212), (7, “my”, 0.11790274), (16, “return”, 0.10876195), (6, '.', 0.0819352), (3, “is”, 0.064508274), (0, “this”, 0.013084531), (12, “has”, 0.0077801645), (8, “son”, 0.0015705228), (15, “to”, −0.023336783), (11, “and”, −0.16156882), (13, “been”, −0.39944094)]