The application discloses a kind of personalized tourism
route recommendation method based on
Transformer-LSTM model, comprising: based on structured
processing, construct
supply side and
demand side characteristic data;
Supply side and
demand side characteristic data are characterized by washing, mapping and pre-
processing;Supply and demand grouping coding structure is constructed;The context dependency in feature sequence is extracted using
Transformer-LSTM
encoder, and the coding representation of each feature group is obtained;According to
supply side coding result and
demand side coding result, supply and demand common decoding initialization is carried out;Based on context dependency and decoding initialization, the LSTM decoding module of the trained personalized tourism
route recommendation model is used to gradually calculate candidate attraction probability;Based on candidate attraction probability, the recommended
route is output by using greedy
inference;According to the recommended route, the recommended explanation result is output.The application fuses
Transformer attention mechanism and LSTM sequence decoding mechanism, improves the accuracy, coherence,
personalization degree and stability of tourism route recommendation result.