Text Information Extraction Based on Simulated Annealing Algorithm and Hidden Markov Model

WANG Ning; LI Shi-jun

Chinese

您当前的位置：

首页 >

文章列表页 >

Text Information Extraction Based on Simulated Annealing Algorithm and Hidden Markov Model

更新时间：2026-09-04

- Text Information Extraction Based on Simulated Annealing Algorithm and Hidden Markov Model
- Vol. 31, Issue 12, Pages: 52-56(2014)
- 作者机构：
  
  武汉大学计算机学院,湖北,武汉,430072
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2014
- 稿件说明：
移动端阅览
王宁, 李石君. 基于模拟退火算法和隐马尔可夫模型的文本信息抽取[J]. 微电子学与计算机, 2014, 31(12): 52-56.

WANG Ning, LI Shi-jun. Text Information Extraction Based on Simulated Annealing Algorithm and Hidden Markov Model[J]. 2014, 31(12): 52-56.
王宁, 李石君. 基于模拟退火算法和隐马尔可夫模型的文本信息抽取[J]. 微电子学与计算机, 2014, 31(12): 52-56. DOI：

WANG Ning, LI Shi-jun. Text Information Extraction Based on Simulated Annealing Algorithm and Hidden Markov Model[J]. 2014, 31(12): 52-56. DOI：

摘要

本文提出了一种基于改进的模拟退火算法和二阶隐马尔可夫模型相结合的信息抽取方法.其中

改进的模拟退火算法在适当的时机增加了重升温过程

提高了局部寻优的搜索效率;二阶隐马尔可夫模型充分考虑了概率与历史状态的关联性

增加了信息抽取的可靠性.实验结果表明

新算法在精确度、召回率和时间性能指标上比基于模拟退火算法和一阶隐马尔可夫模型的信息抽取方法有所提高.

Abstract

An improved combined method embedded with modified simulated annealing algorithm and second-order hidden Markov model was presented.The modified simulated annealing algorithm improves the temperature at the proper time

which increased the efficiency of local search optimization.The second-order hidden Markov model considers the relevance of probability and historical status which improved the reliability of information extraction.Experimental results show that the new method has a better improvement in precision

recall and time performance than the method combined with simulated annealing algorithm and first-order hidden Markov model.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Aerial small object detection algorithm based on improved RT-DETR

Design of ultra-low power real-time clock circuits

A review of large model development: technological evolution from BERT to Deepseek

Implementation and verification of a dual-chain power gating strategy for low power design

Research on the design of blockchain-based AI-generated content traceability framework

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰