Abstract: An encoding method is provided for an encoding apparatus. The method includes obtaining a target paragraph and a preset database, and inputting the target paragraph and preset database into a memory encoding model, obtaining, in an input layer, an original vector set of the target paragraph and a knowledge vector set of the preset database, obtaining, in a first memory layer, a first target sentence matrix according to the original vector set and the knowledge vector set, and obtaining, in an output layer, a paragraph vector of the target paragraph according to the first target sentence matrix, and performing processing based on the paragraph vector.

Abstract: Embodiments of this disclosure include an encoding method and apparatus. The encoding may include obtaining a target paragraph and a context sentence of the target paragraph, and inputting the target paragraph and the context sentence into a memory encoding model. The encoding may further include obtaining an original vector set and a memory vector set in the input layer and obtaining a first target sentence matrix of the original vector set in the memory layer according to the original vector set and the memory vector set. The encoding may further include obtaining a paragraph vector of the target paragraph in the output layer according to the first target sentence matrix and performing processing based on the paragraph vector.

Abstract: An encoding method is provided for an encoding apparatus. The method includes obtaining a target paragraph and a preset database, and inputting the target paragraph and preset database into a memory encoding model, obtaining, in an input layer, an original vector set of the target paragraph and a knowledge vector set of the preset database, obtaining, in a first memory layer, a first target sentence matrix according to the original vector set and the knowledge vector set, and obtaining, in an output layer, a paragraph vector of the target paragraph according to the first target sentence matrix, and performing processing based on the paragraph vector.

Abstract: Embodiments of this disclosure include an encoding method and apparatus. The encoding may include obtaining a target paragraph and a context sentence of the target paragraph, and inputting the target paragraph and the context sentence into a memory encoding model. The encoding may further include obtaining an original vector set and a memory vector set in the input layer and obtaining a first target sentence matrix of the original vector set in the memory layer according to the original vector set and the memory vector set. The encoding may further include obtaining a paragraph vector of the target paragraph in the output layer according to the first target sentence matrix and performing processing based on the paragraph vector.

Abstract: The present disclosure provides a dialog generation method, performed by a human-machine dialog system. The method includes obtaining an input dialog sequence from a dialog client; obtaining associated information related to the input dialog sequence; encoding, by an encoder, the input dialog sequence to obtain an input encoding vector; encoding, by the encoder, the associated information to obtain an associated encoding vector; decoding, by a decoder, the input encoding vector and the associated encoding vector to obtain an output dialog sequence, the output dialog sequence comprising an out-of-vocabulary word corresponding to the associated information; and transmitting the output dialog sequence to the dialog client.

Abstract: A sentence generation method is provided for an electronic device. The method includes obtaining an input sequence, encoding the input sequence to obtain a sentence eigenvector, decoding the sentence eigenvector to obtain a first predetermined quantity of candidate sentence sequences, clustering the first predetermined quantity of candidate sentence sequences to obtain sentence sequence sets of at least two types, screening out a second predetermined quantity of candidate sentence sequences from the sentence sequence sets of at least two types, the second predetermined quantity of candidate sentence sequences including at least two sentence feature types, and determining an output sequence corresponding to the input sequence according to the second predetermined quantity of candidate sentence sequences.