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An Improved Domain Classification Method Combining Prefix Tree and Recurrent Neural Network

A cyclic neural network and classification method technology, applied in natural language processing, the combination of improved prefix tree and cyclic neural network, can solve problems such as poor performance, and achieve the effect of improving accuracy and solving performance problems

Active Publication Date: 2022-06-21
SICHUAN CHANGHONG ELECTRIC CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] This field classification method based on prefix tree and cyclic neural network found in the practice of the project that the performance is not ideal, 80tps, pressure test for 2 hours, 500ms timeout, and 1500+ timeouts will also appear

Method used

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  • An Improved Domain Classification Method Combining Prefix Tree and Recurrent Neural Network
  • An Improved Domain Classification Method Combining Prefix Tree and Recurrent Neural Network
  • An Improved Domain Classification Method Combining Prefix Tree and Recurrent Neural Network

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Embodiment Construction

[0037] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other implementations obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

[0038] In either embodiment, if figure 1As shown, an improved domain classification method combining prefix tree and cyclic neural network of the present invention, here we take 8 categories as an example, including

[0039] Step 1: Build a Recurrent Neural Network Model

[0040] a) Collect user data about 8 fields. Because there are more data in TV, MUSIC, and VIDEO fields, the fields classified by the recurrent neural network are TV, MUSIC, VIDEO, and OTHER,...

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Abstract

The invention discloses an improved domain classification method combining prefix tree and cyclic neural network. By adding new user data, retraining the RNN model and reconstructing the prefix tree, and then redesigning the domain classification algorithm structure according to real user requests, and finally Optimized the weight calculation method of prefix tree features. It successfully solves the performance problem of domain classification and improves the accuracy of classification.

Description

technical field [0001] The invention relates to the technical field of natural language processing, in particular to an improved domain classification method combining prefix tree and cyclic neural network. Background technique [0002] Natural language processing (NLP) is an important direction in the field of computer science and artificial intelligence. Its research can realize various theories and methods for effective communication between humans and computers using natural language. Natural language processing is a science that combines linguistics, computer science, and mathematics. The purpose of natural language processing is to enable computers to "understand" what humans "speak" to it, and then perform some specified tasks. These tasks include spell checking, keyword search, intent recognition, machine translation, dialogue systems, etc. For our Semantic Cloud project, natural language processing is to realize effective communication between humans and televisi...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/35G06F40/289G06F40/295G06F40/30G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/044G06N3/045G06F18/24
Inventor 刘楚雄代秀琼
Owner SICHUAN CHANGHONG ELECTRIC CO LTD