A behavior recognition method based on natural semantic understanding, and a related device. The method comprises: extracting, by means of a word segmentation algorithm in an auto-encoding model, text features from a plurality of sentences in a first document so as to constitute a plurality of first vectors, wherein the text features in each sentence constitute a first vector; training, by means of an attention network in the auto-encoding model, the plurality of first vectors so as to obtain an attention weight of each first vector in the plurality of first vectors; inputting the plurality of first vectors and the attention weight of each first vector in the plurality of first vectors into an LSTM for training so as to generate a first semantic vector; decoding, by means of the LSTM, the first semantic vector so as to obtain a plurality of first decoding vectors; and if the plurality of first decoding vectors and the plurality of first vectors satisfy a pre-set similarity condition, comparing the first semantic vector with a second semantic vector of a second document so as to determine whether there is a target behavior. By means of the method, a target behavior can be determined more accurately.
BEHAVIOR RECOGNITION METHOD BASED ON NATURAL SEMANTIC UNDERSTANDING, AND RELATED DEVICE