Data processing method and device, storage medium and electronic device
A data processing and data technology, applied in the computer field, can solve the problem that the sequence model cannot be modeled for long-term dependencies
Active Publication Date: 2019-09-20
TENCENT TECH (SHENZHEN) CO LTD
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[0006] Embodiments of the present invention provide a data processing method and device, a storage medium, and an electronic device to at least solve the technical problem that the sequence model in the related art cannot model long-term dependencies
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[0025] In order to make those skilled in the art better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only Embodiments are part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
[0026] It should be noted that the terms "first", "second" and the like in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used may be interchanged under appropriate ...
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The invention discloses a data processing method and device, a storage medium and an electronic device. The method comprises: acquiring target sequence data, and the target sequence data comprising multiple groups of data sorted according to a time sequence; sequentially inputting each data in each group of data in the plurality of groups of data into a target neural network model, in a process of processing current data by a target neural network model, processing the current data according to the previous group of data of the current group of data, a previous group of processing results obtained by processing each piece of data in the previous group of data by using the target neural network model, and a previous processing result obtained by processing the previous piece of data of the current data by using the target neural network model; and obtaining a data processing result output by the target neural network model. According to the method, the technical problem that a sequence model cannot model a long-time dependency relationship in the prior art is solved.
Description
technical field [0001] The present invention relates to the field of computers, and in particular, to a data processing method and device, a storage medium and an electronic device. Background technique [0002] Currently, sequence data modeling can be applied to visual processing (eg, video understanding classification, anomalous action detection), text analysis (eg, sentiment classification), dialogue systems, and more. [0003] Methods for sequence modeling can be graphical models, which can be divided into two categories: generative models (generative graphical models) and discriminative models (discriminative graphical models). As an example of a generative model, a Hidden Markov Model can model latent specific characteristics of sequence data in a chain. A discriminative model models the distribution of all class labels from the input data. An example of a discriminative model is a conditional random field. [0004] The sequence model can also be based on a recurrent...
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IPC IPC(8): G06N3/04
CPCG06N3/04G06N3/049G06N3/045G06N3/08G06V10/82G06N3/044
Inventor 付灿苗曹琼裴文杰沈小勇戴宇荣贾佳亚
Owner TENCENT TECH (SHENZHEN) CO LTD