Scientific Programming / 2020 / Article / Alg 1

Research Article

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

Algorithm 1

Text sentiment analysis algorithm based on W-RNN.
Input:
  CWE-word vector
  CTR-training corpus
  CTE-test corpus
Output: Prediction results of test samples.
(1)pro_processing (CWE)
(2)Dict = word2vec (CWE)//create the word vector dictionary Dict
(3)batches [] ⟵ Divide (CTR)//divide CTR into several batches
(4)for i ⟵ 0 to epochs do
(5) for j ⟵ 0 to length (batches) do
(6)  for k ⟵ 0 to length (batches[j]) do
(7)    ⟵ FindWord (batches [j][k])//find the words vector in batches[j][k] from Dict
(8)   h ⟵ //the feature vector h is extracted from
(9)   h′ ⟵ Measure (h)//measure the impact of h
(10)    ⟵ Sort (, h’)//sort words vector in descending order according to h
(11)   c ⟵ ExtractFeature ()//extract secondary feature from the word vector
(12)   z ⟵ Softmax (c)//Get the prediction results of samples by Softmax classifier
(13)   end for
(14)   Update (z, , (b)//update parameters and b of the model by backpropagation
(15)  end for
(16)end for
(17)for i ⟵ 0 to length (CTE) do
(18)   ⟵ FindWord (CTE [i])
(19)  h ⟵ 
(20)  h’ ⟵ Measure (h)
(21)   ⟵ Sort (, h’)
(22)  c ⟵ ExtractFeature ()
(23)  output ⟵ Softmax (c)
(24)end for

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