Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Free text generation method

A text and vector technology, applied in the field of liberalized text generation, can solve problems such as inability to achieve, and achieve the effect of maintaining consistency and ensuring robustness

Inactive Publication Date: 2017-05-31
TSINGHUA UNIV +1
View PDF4 Cites 21 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The technical problem to be solved by the present invention is how to overcome the text generation model in the prior art that cannot combine the advantages of SMT and traditional NN, that is, it is impossible to train the mapping information of words and the semantic information of words while training NN. defect

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Free text generation method
  • Free text generation method
  • Free text generation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0052] Such as figure 1 As shown, the present invention provides a kind of free text generation method, comprises the following steps:

[0053] S1. Combining keywords input by the user into character strings, there are several keywords, wherein one keyword corresponds to one word vector;

[0054] The neural network mentioned in this embodiment is an advanced recurrent neural network GRU (Gated Recurrent Unit) in recurrent neural networks (Recurrent Neural Networks...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a free text generation method. The method comprises the following steps: S1, key words input by a user are combined into a character string; S2, the character string is encoded into a group of word vectors with the dimension being i through a first recurrent neutral network, and implicit vectors are generated according to the word vectors; S3, a candidate set of the t word is generated through a second recurrent neutral network according to the word vectors and the implicit vectors, the probability distribution vector of the candidate set of the t word is predicted, and t is larger than or equal to 1; S4, the word with the largest probability distribution in the candidate set is output as a predicted word Yt according to the text format, and all texts are generated through loop iteration. According to the text generation method, mapping information and semantic information of words are trained simultaneously, texts in various formats can be used for learning, the data sparseness problem is solved, and texts in any length and any sentence pattern can be generated.

Description

technical field [0001] The invention relates to the field of computer artificial intelligence, in particular to a method for generating free text. Background technique [0002] Automatic text generation is considered to be an important symbol of contemporary machine intelligence, because people need a strong imagination when creating text, the machine must be able to "learn" the way the article is written and "simulate" the creative ability of the human brain, so it is extremely difficult . There are two traditional methods of text generation, including statistical machine translation probability model (Statistical Machine Translation, SMT) and neural network model (Neural Networks, NN). [0003] The Statistical Machine Translation Probability Model (SMT) is a technology that uses a machine to translate a sentence to be translated input by a user to obtain a target sentence. Machine translation is based on the following principle: the translation of the source sentence t...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F17/27G06N3/04
CPCG06F40/274G06N3/045
Inventor 王琪鑫王东游世学骆天一邢超杜新凯
Owner TSINGHUA UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com