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

Man-machine dialogue method and man-machine dialogue device based on knowledge graph

A technology of knowledge graph and human-computer dialogue, which is applied in the fields of human-computer dialogue devices, computer equipment and readable storage media, and can solve problems such as providing knowledge answers and being unable to use users.

Pending Publication Date: 2019-11-26
PING AN TECH (SHENZHEN) CO LTD
View PDF0 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, such models are trained on historical corpus data to make immediate responses to conversations, but cannot provide users with relevant knowledge answers

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
  • Man-machine dialogue method and man-machine dialogue device based on knowledge graph
  • Man-machine dialogue method and man-machine dialogue device based on knowledge graph
  • Man-machine dialogue method and man-machine dialogue device based on knowledge graph

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0064] Refer to figure 1 , Shows a flow chart of the steps of the human-machine dialogue method based on the knowledge graph in the first embodiment of the present invention. It can be understood that the flowchart in this method embodiment is not used to limit the order of execution of the steps. It should be noted that, in this embodiment, the human-machine dialogue device 2 is used as the execution subject for exemplary description. details as follows:

[0065] Step S100: Obtain the sentence input by the user.

[0066] Step S102: Perform word vector processing on the sentence.

[0067] Step S104, input the processing result into the convolutional neural network model.

[0068] In a specific embodiment, when the sentence input by the user is obtained, the sentence is subjected to word segmentation processing, and then the word segmentation processing result is input into the word2vector model to generate the corresponding word vector, and then the word vector is input to the convo...

Embodiment 2

[0087] See figure 2 , Shows a schematic diagram of the hardware architecture of the human-machine dialogue device of the second embodiment of the present invention. The human-machine dialogue device 2 includes, but is not limited to, a memory 21, a processing 22, and a network interface 23 that can communicate with each other through a system bus. figure 2 Only the human-machine dialogue device 2 with components 21-23 is shown, but it should be understood that it is not required to implement all the illustrated components, and more or fewer components may be implemented instead.

[0088] The memory 21 includes at least one type of readable storage medium, the readable storage medium includes flash memory, hard disk, multimedia card, card type memory (for example, SD or DX memory, etc.), random access memory (RAM), static memory Random access memory (SRAM), read only memory (ROM), electrically erasable programmable read only memory (EEPROM), programmable read only memory (PROM), ...

Embodiment 3

[0092] See image 3 , Shows a schematic diagram of program modules of the man-machine dialogue system of the third embodiment of the present invention. In this embodiment, the human-machine dialogue system 20 may include or be divided into one or more program modules. The one or more program modules are stored in a storage medium and executed by one or more processors to complete The invention can realize the above-mentioned human-machine dialogue method based on the knowledge graph. The program module referred to in the embodiment of the present invention refers to a series of computer program instruction segments capable of completing specific functions, and is more suitable for describing the execution process of the human-machine dialogue system 20 in the storage medium than the program itself. The following description will specifically introduce the functions of each program module in this embodiment:

[0093] The obtaining module 201 is used to obtain sentences input by t...

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 embodiment of the invention provides a man-machine dialogue method based on a knowledge graph. The man-machine dialogue method comprises the steps: obtaining statements input by a user; performingword vector processing on the statement; inputting a processing result into the convolutional neural network model; utilizing the convolutional neural network model to identify the intention of the statement; carrying out slot prediction on words in the statement; inputting the intention and the slot position prediction result into a knowledge graph; determining the corresponding relationship ofthe words according to the corresponding relationship among the entities in the knowledge graph; and searching the knowledge graph, and outputting the content corresponding to the relationship in theknowledge graph so as to realize man-machine conversation. Through the embodiment of the invention, questions of common knowledge and open fields can be answered, and dialogues can be actively initiated.

Description

Technical field [0001] The embodiments of the present invention relate to the field of big data, and in particular to a human-machine dialogue method, a human-machine dialogue device, a computer device and a readable storage medium based on a knowledge graph. Background technique [0002] The intelligent question answering system accurately locates the question knowledge required by the user in the form of one question and one answer, and provides users with personalized information services through interaction with the users. [0003] The traditional human-machine dialogue system is mainly based on the sequence to sequence (seq2seq) model. However, this type of model is trained based on historical corpus data to make immediate responses based on dialogue, but it cannot provide users with relevant knowledge answers. This solution attempts to realize a man-machine dialogue system through the combination of a knowledge graph and a task-based dialogue model. Summary of the invention...

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): G06F16/33G06F16/332G06F16/36G06N3/04G06N3/08
CPCG06F16/3344G06F16/3329G06F16/367G06N3/08G06N3/045Y02D10/00
Inventor 金戈徐亮
Owner PING AN TECH (SHENZHEN) CO LTD
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