  Aiming at the limitation that deep long and short-term memory network(DLSTM)
algorithm cannot perform parallel computing and cannot obtain global
information, in this paper, feature extraction and feature processing are
firstly carried out according to the characteristics of eye movement data and
tracking data, then by introducing a convolutional neural network (CNN) into a
deep long and short-term memory network, developed a new network structure and
designed a fusion strategy, an eye tracking data fusion algorithm based on long
and short-term memory network is proposed. The experimental results show that
compared with the two fusion algorithms based on deep learning, the algorithm
proposed in this paper performs well in terms of fusion quality.
