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Entity identification data enhancement method and system based on knowledge graph

A technology of entity recognition and knowledge graph, which is applied in the field of entity recognition data enhancement based on knowledge graph, computer equipment and readable storage media, can solve the problems of lack of data in vertical fields, low recall rate of question entity recognition, low recall rate, etc.

Pending Publication Date: 2019-12-20
PING AN TECH (SHENZHEN) CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Data sparsity makes the model unable to be fully trained, which makes the model prone to overfitting and poor generalization performance, especially in actual business scenarios, the recall rate is too low, and the entities in the questions input by the user cannot be extracted well
[0004] Therefore, the present invention aims to solve the problems of lack of data in the vertical field, difficulty in building a question answering system, and low recall rate of question entity recognition

Method used

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  • Entity identification data enhancement method and system based on knowledge graph
  • Entity identification data enhancement method and system based on knowledge graph
  • Entity identification data enhancement method and system based on knowledge graph

Examples

Experimental program
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Embodiment 1

[0071] refer to figure 1 , shows a flow chart of the steps of the knowledge graph-based entity recognition data enhancement method according to Embodiment 1 of the present invention. It can be understood that the flowchart in this method embodiment is not used to limit the sequence of execution steps. It should be noted that this embodiment uses the computer device 2 as an execution subject for exemplary description. details as follows:

[0072] Step S100, collecting question answer data in a certain field from the question answer database, wherein the certain field includes at least the medical field and / or the tourism field.

[0073] For example: if it is necessary to identify entities in the medical field, collect question-and-answer data in the medical field. If it is necessary to identify entities in the tourism field, collect question-and-answer data in the tourism field. An entity refers to something that is distinguishable and exists independently, such as hyperlip...

Embodiment 2

[0094] see figure 2 , shows a schematic diagram of the hardware architecture of the computer device according to Embodiment 2 of the present invention. The computer 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 computer device 2 is shown with components 21-23, but it should be understood that implementation of all of the illustrated components is not required and that more or fewer components may instead be implemented.

[0095] The memory 21 includes at least one type of readable storage medium, and the readable storage medium includes a flash memory, a hard disk, a multimedia card, a card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static Random Access Memory (SRAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), Programmable Read Only Memory (PROM), Magnetic Memory,...

Embodiment 3

[0099] see image 3 , shows a schematic diagram of program modules of a knowledge graph-based entity recognition data enhancement system according to Embodiment 3 of the present invention. In this embodiment, the knowledge map-based entity recognition data enhancement system 20 may include or be divided into one or more program modules, one or more program modules are stored in a storage medium, and processed by one or more processors Execute to complete the present invention, and realize the above knowledge map-based entity recognition data enhancement method. The program module referred to in the embodiment of the present invention refers to a series of computer program instruction segments capable of accomplishing specific functions, which is more suitable than the program itself for describing the execution process of the knowledge graph-based entity recognition data enhancement system 20 in the storage medium. The following description will specifically introduce the ...

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Abstract

The invention provides an entity identification data enhancement method based on a knowledge graph. The entity identification data enhancement method comprises the steps of collecting the question andanswer data of a determined field; identifying the annotation information of the question and answer data, and identifying an intention of the question and answer data according to the annotation information to establish a structure of an entity in the question and answer data in the knowledge graph; identifying a first entity related to the intention from the entities, and summarizing the firstentity into a first concept to obtain a first question and answer data template, the first question and answer data template comprising the first concept and a relational word; performing word segmentation on the relational words to obtain the segmented words; according to the correlation degree of each word segmentation word and the intention, endowing each word segmentation word with a corresponding weight to obtain the reserved word segmentation words; and combining the reserved segmented words with the first concept to generate a second question and answer data template, and adding the second question and answer data template into a question and answer database. According to the invention, the construction speed of a question-answering system in the vertical field can be improved, andthe recall rate of the question entity identification can be effectively improved.

Description

technical field [0001] Embodiments of the present invention relate to the field of big data, and in particular to a method, system, computer equipment, and readable storage medium for enhancing entity recognition data based on knowledge graphs. Background technique [0002] Knowledge graph is to use visualization technology or structured way to describe entity and entity relationship knowledge, and provide high-quality knowledge retrieval service for search engine users. Knowledge graph is the prototype of building next-generation search engine, making search more semantic and intelligent. Knowledge graphs need to identify entities. Most of the current knowledge graphs are researched from traditional fields by identifying the entities mentioned in user questions. For example, taking the medical field as an example, entities that need to be identified generally include drugs, diseases, and symptoms. Based on the result of entity recognition, the question answering system ca...

Claims

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Application Information

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IPC IPC(8): G06F17/27G06F16/36
CPCG06F16/367Y02A90/10
Inventor 梁欣朱威
Owner PING AN TECH (SHENZHEN) CO LTD
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