Performances of methods.

Performances of methods.</p

The F1 scores for different number of heads for multi-attention.

The F1 scores for different number of heads for multi-attention.</p

The losses of the training process before and after the optimization of loss function.

A blue and an orange dot lines represent losses of training and validation set before optimization, whereas a yellow and a light blue lines represent losses of training and validation set after optimization. A gray line is the line when loss = 0.05.</p

S1 Dataset -

(ZIP)</p

mTL-Bi-LSTM-MA-CRF model.

Weights of the embedding, the Bi-LSTM, the multi-attention, and the CRF are pre-trained and shared with transfer learning. A weight of the adaptation layer is individually trained and a weight of the CRF is fine-tuned.</p

Examples of CWS of methods.

Examples of CWS of methods.</p

Comparison of softsign function and tanh function.

A red line represents tanh, a blue line represents derivative of tanh, a green line represents softsign, and a yellow line represents derivative of softsign.</p

Methodological framework.

A hybrid method and related CWS model of mTL-Bi-LSTM-MA-CRF are put forward for QM-related texts and validated with four sets of experiments.</p

Accuracy of long words of methods.

Accuracy of long words of methods.</p

The F1 scores for different word embedding dimensions.

A black dotted line and a blue dotted line represent the F1 score of the proposed model and the Bi-LSTM-MA-CRF model, respectively. The vertical axis of the black line is on the left, whereas the vertical axis of the blue line is on the right.</p