The invention discloses an implementation method of a fusion network question and answer
system based on a multi-attention mechanism, which comprises the following steps of constructing a question andanswer
system network model, preprocessing an
original data set to obtain a standby
data set, and performing text
length distribution analysis; subjecting text in standby
data set to one-hot vector representation, using a CBOW model to
train one-hot word vector and forming a word2vec
word list; adjusting the sequence length of each
sentence in the text, and adding a
sentence end mark; training the word2vec vector by using an ELMO
language model to obtain an ELMO word vector; encoding the ELMO vector to obtain a
sentence vector; performing coarse-fine
granularity attention on the sentence vectors respectively to obtain memory vectors and attention vectors based on each word; carrying out vector splicing to obtain expression vectors based on words and sentences; and decoding an answer representing the
vector generation question sentence. According to the method, the representation ability of sentences is improved through an ELMO
language model; and various attention mechanisms are fused, so that the
decision making accuracy of the
system is improved, and the
interpretability of the system is enhanced.