Self-adaptive structure adjusting method and system of machine learning data index structure

A data indexing and machine learning technology, applied in machine learning, other database indexing, network data retrieval, etc., can solve problems such as incomplete research on machine learning indexing structure, reduce cache access slow, avoid performance impact, node load balanced effect

Inactive Publication Date: 2020-06-19
SHANGHAI JIAO TONG UNIV
View PDF4 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, the previous work on the research of machine learning index structure is not comprehensive, and there is still a certain gap

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
  • Self-adaptive structure adjusting method and system of machine learning data index structure

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0041] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0042] According to an adaptive structure adjustment method of a machine learning data index structure provided by the present invention, comprising:

[0043] Step of selecting nodes: select the nodes in the machine learning data index structure one by one according to the preset node number sequence;

[0044] Step of analyzing nodes: analyze the selected nodes, and perform corresponding structural adjustment operations according to the amount of cached data in the node and the size of the error range: if...

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 provides a self-adaptive structure adjustment method and system for a machine learning data index structure. The method comprises the following steps: a node selection step: selecting nodes in the machine learning data index structure one by one according to a preset node number sequence; a node analysis step: analyzing the selected nodes, and executing corresponding structure adjustment operation according to the cache data volume in the nodes and the error range size: if the cache data volume in the nodes or the prediction error of the machine learning model in the nodes is toolarge, executing a node splitting step; if the cache data volume and the error range in the node and the adjacent node are both too small, the two nodes execute a node merging step; otherwise, endingthe process. According to the fine-grained machine learning index structure adjustment method provided by the invention, compared with retraining of all data, the number of retrained models can be reduced, and the influence on performance of irrelevant models and cache during structure adjustment is avoided.

Description

technical field [0001] The invention relates to the field of data indexing in data storage systems, in particular to a method and system for adaptive structure adjustment of machine learning data indexing structures. Background technique [0002] In today's big data era, the scale of data is getting larger and larger, and databases are being used more and more, and new challenges are constantly encountered in the process, mainly including higher requirements for low-latency and high-throughput indexes, etc. . The index is an additional structure derived from the original data of the database, including many keywords, each keyword points to a piece of data, the index can quickly query the data corresponding to a certain keyword, and the index can be used in the database to speed up data query. [0003] Machine learning studies how to use algorithms and statistical models to enable computer systems to effectively perform a specific task based on the observation and inference ...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/901G06F16/903G06F16/907G06F16/957G06K9/62G06N20/00
CPCG06F16/901G06F16/907G06F16/90335G06N20/00G06F16/9574G06F18/214
Inventor 王肇国王友运唐楚哲董致远胡淦森陈海波
Owner SHANGHAI JIAO TONG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products