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

Incidence relation excavation method for text-oriented knowledge unit

A technology of knowledge units and associations, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of large amount of calculation and high computational complexity

Inactive Publication Date: 2012-05-02
XI AN JIAOTONG UNIV
View PDF5 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The methods described in the above three related patent inventions all need to classify all possible relationship pairs, which has the disadvantages of large amount of calculation and high computational complexity

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
  • Incidence relation excavation method for text-oriented knowledge unit
  • Incidence relation excavation method for text-oriented knowledge unit
  • Incidence relation excavation method for text-oriented knowledge unit

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0055] The specific technical solutions of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0056] Such as figure 2 As shown, the mining method of the text-oriented knowledge unit association relationship of the present invention comprises 3 steps, and its concrete process is:

[0057] 1. Text association mining:

[0058] Text is a carrier for storing knowledge units. Knowledge unit refers to the smallest unit with complete knowledge expression. There is an association relationship (also known as learning dependency) between knowledge units, and it is often necessary to learn some other knowledge units before learning a knowledge unit. For example, in plane geometry, it is necessary to learn the knowledge unit "definition of triangle" before learning the knowledge unit "theorem of interior angles of a triangle", so the knowledge unit "theorem of interior angles of a triangle" and knowledge unit "definition of ...

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 an incidence relation excavation method for a text-oriented knowledge unit. The method comprises the following steps of: (1) carrying out aggregation for a text set, finding a text subset with a similar theme, on the base, utilizing nonsymmetry of term distribution in the text and excavating a linear incidence relation between texts; (2) utilizing locality of the incidence relation of a knowledge unit pair, and generating a candidate knowledge unit pair; (3) based on characteristics of term word frequency, distance and semantic types of the knowledge unit pair, carrying out a bi-level classification for the candidate knowledge unit pair, and distinguishing the incidence relation of the knowledge unit pair. In the incidence relation excavation method, numbers of candidate knowledge units can be greatly reduced, and time complexity of relation excavation can be effectively reduced on the premise that accuracy is ensured.

Description

technical field [0001] The invention relates to a retrieval method of network data, in particular to a text-oriented knowledge unit correlation mining method. Background technique [0002] With the rapid development and increasing popularity of computer networks, the information on the Internet is increasing exponentially. The information age has brought massive amounts of digital texts, and the increasing accumulation of data has made it increasingly difficult to obtain information. People's time and energy are limited. Faced with such a huge digital resource, it is impossible to quickly and accurately find useful information from a large amount of data. Therefore, automated extraction tools are needed to help people retrieve massive data. After a novelty search, the applicant did not find a patent for a text-oriented knowledge unit association relationship mining method, so three patents related to relationship mining were retrieved, which are: [0003] 1. Relation extra...

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): G06F17/30
Inventor 刘均郑庆华叶俊挺
Owner XI AN JIAOTONG 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