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

An Ontology-Based Semantic Association Retrieval Method for Medical Documents

A semantic association and document technology, applied in the field of medical document analysis and retrieval, can solve the problems of insufficient intelligence of retrieval results, inability to estimate the relevance of query result documents, high user requirements, etc., to achieve personalized retrieval, expand user queries, and enhance documents semantic effect

Active Publication Date: 2018-08-28
ZHEJIANG UNIV
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0013] The present invention mainly solves the technical problems existing in the prior art, such as high requirements for users, insufficient intelligence of retrieval results, and inability to estimate document correlation of query results, etc., and provides a method that can take into account the unique structural information of XML documents and medical documents. Special semantic information, ontology-based medical document semantic association retrieval method with good retrieval effect

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
  • An Ontology-Based Semantic Association Retrieval Method for Medical Documents
  • An Ontology-Based Semantic Association Retrieval Method for Medical Documents
  • An Ontology-Based Semantic Association Retrieval Method for Medical Documents

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0050] Embodiment: the ontology-based medical document semantic association retrieval method of this embodiment, such as figure 1 As shown, the algorithm flow is mainly composed of four links: document analysis, document storage, query association and document retrieval. The document analysis link mainly consists of three parts: XML document analysis, D2R semantic conversion and XML document structure analysis; the document storage link mainly constructs XML document clustering ontology; the query association link includes two parts: user query establishment and user query expansion; The document retrieval link is responsible for the core task of this research, that is, XML document retrieval. Each part will be described in detail below, and the symbol conventions and meanings used in the method will be explained first.

[0051] Symbol conventions and meanings:

[0052] 1. A document set consisting of all physical documents, denoted as C;

[0053] 2. Each physically existin...

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 method for searching semantic association of medical documents based on the ontology. The method comprises A. analyzing XML documents and identifying marks of the XML documents; B. sorting the marks of the XML documents according to a Rock sorting algorithm based on links, describing a sorting result using the ontology web language (OWL), and constructing an XML document cluster ontology; C. converting analyzed marks of the XML documents and text data into examples of the XML document cluster ontology through a D2R semantic data converter, and storing in a semantic web resource description framework triple mode; and D. searching using a vector searching algorithm based on the simple path Xpath. The method can be used for searching similarity of full texts and estimating correlation of a search result, a user can obtain a complete and accurate search result with no need to be very familiar with documents. The method is used for storing and searching medical documents.

Description

technical field [0001] The invention relates to the field of medical document analysis and retrieval, in particular to an ontology-based semantic correlation retrieval method for medical documents. Background technique [0002] Ontology, knowledge ontology is a standardized description of domain concepts and the relationship between concepts. This description is standardized, clear, formalized, and shareable. "Unambiguous" means that the types of concepts employed and the constraints to which they apply are clearly defined. "Formalization" means that the knowledge ontology is computer-readable (that is, it can be processed by a computer); "shared" reflects that the knowledge ontology should capture the unanimously recognized knowledge in this field, reflecting the recognized concept set in related fields, that is, the knowledge ontology Consensus aimed at groups rather than individuals. The goal of knowledge ontology is to capture the knowledge of related fields, provide a...

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 Patents(China)
IPC IPC(8): G06F17/30
CPCG06F16/81G06F16/83G06F16/93
Inventor 李劲松张艺帆田雨苟玲李鹏飞
Owner ZHEJIANG 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