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

Natural language-oriented content diversification searching method

A natural language and search method technology, which is applied in the field of natural language-oriented content diversification search, can solve the problems of inability to calculate language, excessive query calculation and difficulty in understanding query results, etc., so as to improve query friendliness and optimize users. Experience, the effect of enhancing the user experience

Active Publication Date: 2018-10-02
SICHUAN CHANGHONG ELECTRIC CO LTD
View PDF5 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

When using knowledge graphs, it is easy to encounter the following problems: First, since user queries are usually expressed in natural language, such languages ​​cannot be directly calculated using knowledge graphs.
[0005] (a) Due to the large input and high computational complexity, the calculation amount of query calculation is often too large;
[0006] (b) Since there may be a large number of matching results in the query pattern graph in the knowledge graph, it is difficult to understand the query results;

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
  • Natural language-oriented content diversification searching method
  • Natural language-oriented content diversification searching method
  • Natural language-oriented content diversification searching method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0053] Such as figure 1 As shown, a natural language-oriented content diversification search method includes the following steps:

[0054] Step s1: Construct a knowledge graph, using entities as nodes and the "entity-entity" relationship as edges, to establish a knowledge graph G;

[0055] Step s2: Perform entity extraction on the natural language query sentence input by the user. This solution uses CRF++ to realize entity extraction;

[0056]Step s3: If the extracted entity does not exist in the knowledge graph, use the method of similarity calculation to obtain entities similar to it;

[0057] Step s4: judge the relationship between entities;

[0058] Step s5: Construct a query pattern graph Q based on the entity and the "entity-entity" relationship, and mark the "query focus";

[0059] Step s6: Match the query pattern graph Q and the knowledge graph G through the subgraph isomorphism algorithm to obtain a set of "objects" matching the "query focus";

[0060] Step s7: Se...

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 natural language-oriented content diversification searching method. The method mainly includes: understanding a query statement of a user, and then converting a natural-language query into a query pattern graph with ''query focus'' through technology of entity recognition, text representation, entity relationship extraction and the like; then using a method of structure matching to carry out matching calculation on a query pattern graph and a knowledge map to obtain a series of results satisfying a query requirement; and finally, obtaining Top-k query results, which are highly related to the ''query focus'' and diversified, through diversification calculation, and thus better satisfying the query requirement of the user. According to the method of the invention, more diversified retrieval contents can be provided for the user, and searching speed is high.

Description

technical field [0001] The present invention relates to the technical field of search methods, in particular to a natural language-oriented content diversification search method. Background technique [0002] Knowledge graph organizes massive information in a structured way and efficiently provides answers to users' queries. Therefore, it has attracted extensive attention in academia and industry in recent years. In the knowledge graph, the query calculation mainly adopts the method of structural matching. That is, given a query pattern graph and a knowledge graph, find all matches in the knowledge graph that match the query pattern graph. [0003] The key to query knowledge graph lies in query comprehension and query calculation. The following problems are mainly encountered when using knowledge graphs: First, since user queries are usually expressed in natural language, such languages ​​cannot be directly calculated using knowledge graphs. Therefore, it is necessary to ...

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 王欣杨兰展华益孙锐钟吉英赵亮谭斌许洛
Owner SICHUAN CHANGHONG ELECTRIC 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