吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

一种融合PLSA模型和树模型的文本病历语义分析新方法

黄文博1,2, 燕杨1,2, 李博3   

  1. 1. 长春师范大学 计算机科学与技术学院, 长春 130032; 2. 吉林大学 通信工程学院, 长春 130012;3. 深圳电信研究院, 广东 深圳 518048
  • 收稿日期:2013-03-08 出版日期:2013-07-26 发布日期:2013-08-06
  • 通讯作者: 燕杨 E-mail:yy4992@sina.com

A New Method of Text Medical Records Semantic AnalysisBased on Merging PLSA Model and Tree Model

HUANG Wenbo1,2, YAN Yang1,2, LI Bo3   

  1. 1. College of Computer Science and Technology,  Changchun Normal University, Changchun 130032, China;2. College of Communication Engineering, Jilin University, Changchun 130012, China;3. Shenzhen Institute of Telecommunications, Shenzhen 518048, Guangdong Province, China
  • Received:2013-03-08 Online:2013-07-26 Published:2013-08-06
  • Contact: YAN Yang E-mail:yy4992@sina.com

摘要:

将文本语义分析领域中的概率潜语义分析(PLSA)模型和语义树模型进行融合, 设计一种新模型, 并将其应用在文本病历语义分析上, 较好地解决了文本病历语义分析过程中存在的“多词一义”情况, 降低了语义维度, 简化了窗口语义树的结构. 通过语义分解和语义检索实验证明了该模型在文本病历语义分析上的优势.

关键词: PLSA-tree模型, 文本病历, 语义分析, 新方法

Abstract:

We designed a new model via merging probability latent semantic analysis (PLSA) model and tree model, and applied it to the semantic analysis of text medical records. We solved the problem of “one meaning of multiword combination”  in the semantic analysis process of medical records so as to
reduce the semantic dimension and simplify the structure of the window semantic tree. The experiment of semantic decomposition and semantic retrieval effectively shows the advantages of PLSAtree model in the semantic analysis of text medical records.

Key words: PLSAtree model, text medical records, semantic analysis, new method

中图分类号: 

  • TP391.1