计算机科学 ›› 2017, Vol. 44 ›› Issue (Z6): 141-145.doi: 10.11896/j.issn.1002-137X.2017.6A.033

• 智能计算 • 上一篇    下一篇

基于SDAs的人物关系抽取方法研究

珠杰,洪军建   

  1. 西藏大学计算机科学系 拉萨850000,西藏大学计算机科学系 拉萨850000
  • 出版日期:2017-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金项目(61262058),西藏大学高原学者-珠杰项目资助

Research on Method of Personal Relation Extraction under SDAs

ZHU Jie and HONG Jun-jian   

  • Online:2017-12-01 Published:2018-12-01

摘要: 针对人物关系语料缺乏的问题,研究了基于互动百科的自动标注方法;针对传统浅层机器学习模型特征表示能力差的问题,提出了基于深度神经网络模型SDAs的人物关系抽取方法。重点研究了多个特征组合的人物关系抽取效果以及不同深度SDAs网络的人物关系抽取效果。根据实验分析,F系数可达到73.75%。

关键词: 社会网络,人物关系抽取,降噪自动编码器,深度学习

Abstract: For the lack of corpus issue in personal relation,this paper studied the methods of automatic tagging based on HUDONG pedia;for poor ability to express feature issue in shallow machine learning models,we proposed the method of personal relation extraction under deep learning model SDAs and focused on the effect of personal relation extraction with combination features and effect of personal relation extraction with different depths in SDAs network. F factor can reach 73.75% through experiment analysis.

Key words: Social network,Extraction of personal relation,SDAs,Deep learning

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