Model training method and device and text intention recognition method and device

An intent and model technology, applied in the field of text intent recognition devices, can solve the problem that the intent category cannot be automatically determined and the accuracy is low, and achieve the effects of high recognition rate, improved accuracy, and strong generalization ability.

Active Publication Date: 2018-04-20
BEIJING QIYI CENTURY SCI & TECH CO LTD
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AI Technical Summary

Problems solved by technology

At present, the traditional machine learning-based intention recognition method has disadvantages such as low accuracy and the inability to automatically determine the intention category.

Method used

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  • Model training method and device and text intention recognition method and device
  • Model training method and device and text intention recognition method and device
  • Model training method and device and text intention recognition method and device

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Embodiment Construction

[0068] In order to make the above objects, features and advantages of the present invention more comprehensible, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific embodiments.

[0069] refer to figure 1 , shows a flow chart of the steps of Embodiment 1 of a model training method of the present invention, which may specifically include the following steps:

[0070] Step 101, obtaining multiple text corpora;

[0071] In the embodiment of the present invention, the model may include a convolutional neural network model, the convolutional neural network model is equivalent to a classifier, and the category value set according to the user's input is output according to the trained convolutional neural network model; specifically , the convolutional neural network model can include a word embedding layer, a convolutional layer, a pooling layer and a fully connected layer. The word embedding layer is mainly use...

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Abstract

Embodiments of the invention provide a model training method and device and a text intention recognition method and device. The model training method comprises the following steps of: obtaining a plurality of text corpuses; respectively carrying out word segmentation and entity recognition on the plurality of text corpuses so as to obtain a seed dictionary and a vocabulary; clustering the seed dictionary and the vocabulary to obtain a plurality of intention categories; in a training, mapping a word vector into a multi-dimensional matrix; obtaining a maximum convolution vector from the multi-dimensional matrix; inputting the maximum convolution vector to a full connection layer; setting the intention categories as hidden nodes of the full connection layer and outputting category values; andwhen the training of a plurality of word vectors is finished, obtaining a model which is repeatedly trained. The invention discloses a word vector-based intention category determination method whichis good at discovering new intention categories when being compared traditional artificial setting and enumerating method; and by adoption of the trained model, the text intention recognition rate ishigher.

Description

technical field [0001] The invention relates to the technical field of computers, in particular to a model training method, a text intent recognition method, a model training device, and a text intent recognition device. Background technique [0002] Machine learning (Machine Learning, ML) is a multi-field interdisciplinary subject, involving probability theory, statistics, approximation theory, convex analysis, algorithm complexity theory and other disciplines. Specializes in the study of how computers simulate or implement human learning behaviors to acquire new knowledge or skills, and reorganize existing knowledge structures to continuously improve their performance. [0003] Machine learning is the core of artificial intelligence and the fundamental way to make computers intelligent. Its application pervades all fields of artificial intelligence, mainly using induction and synthesis rather than deduction. Machine learning is the science of getting computers to behave w...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06K9/62
CPCG06F16/35G06F16/374G06F18/214
Inventor 鲍新平丁希晨
Owner BEIJING QIYI CENTURY SCI & TECH CO LTD
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