Tencent Technology (shenzhen) Company Limited

Baosong Yang

Zhaopeng Tu

Xing Xing Wang

Tong Zhang

Embodiments of this disclosure disclose an information processing method, apparatus and a non-transitory computer readable medium. The method includes: obtaining a target text sequence corresponding to to-be-processed text information; obtaining a context vector according to the target text sequence; determining a logical similarity corresponding to the target text sequence according to the context vector and the target text sequence; and encoding the target text sequence corresponding to target text information by using the logical similarity to obtain a text encoding result. In this embodiment of this disclosure, a context vector related to a discrete sequence is used to encode the discrete sequence, to strengthen the dependence between elements in the discrete sequence, thereby enhancing the performance of a neural network model and improving the learning capability of the model.

Information processing method and apparatus, and storage medium

The present disclosure describes a method, apparatus, and storage medium for generating network representation for a neural network. The method includes obtaining a source-side vector sequence corresponding to an input sequence. The method further includes performing linear transformation on the source-side vector sequence, to obtain a request vector sequence, a key vector sequence, and a value vector sequence corresponding to the source-side vector sequence; calculating a logical similarity between the request vector sequence and the key vector sequence; constructing a local strength matrix according to the request vector sequence; performing nonlinear transformation based on the logical similarity and the local strength matrix, to obtain a local strength attention weight distribution corresponding to elements in the input sequence; and fusing value vectors in the value vector sequence according to the local strength attention weight distribution, to obtain a network representation sequence corresponding to the input sequence.

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Shenzhen, China

Baosong Yang