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融合扩展信息瓶颈理论的话题关联检测方法研究

杨玉珍 刘培玉 费绍栋 张成功

杨玉珍, 刘培玉, 费绍栋, 张成功. 融合扩展信息瓶颈理论的话题关联检测方法研究. 自动化学报, 2014, 40(3): 471-479. doi: 10.3724/SP.J.1004.2014.00471
引用本文: 杨玉珍, 刘培玉, 费绍栋, 张成功. 融合扩展信息瓶颈理论的话题关联检测方法研究. 自动化学报, 2014, 40(3): 471-479. doi: 10.3724/SP.J.1004.2014.00471
YANG Yu-Zhen, LIU Pei-Yu, FEI Shao-Dong, ZHANG Cheng-Gong. A Topic Link Detection Method Based on Improved Information Bottleneck Theory. ACTA AUTOMATICA SINICA, 2014, 40(3): 471-479. doi: 10.3724/SP.J.1004.2014.00471
Citation: YANG Yu-Zhen, LIU Pei-Yu, FEI Shao-Dong, ZHANG Cheng-Gong. A Topic Link Detection Method Based on Improved Information Bottleneck Theory. ACTA AUTOMATICA SINICA, 2014, 40(3): 471-479. doi: 10.3724/SP.J.1004.2014.00471

融合扩展信息瓶颈理论的话题关联检测方法研究

doi: 10.3724/SP.J.1004.2014.00471
基金项目: 

国家自然科学基金(60873247),山东省自然基金(ZR2012FM038),山东省科技发展计划(2012GGB01194)资助

详细信息
    作者简介:

    刘培玉 山东师范大学信息科学与工程学院教授.主要研究方向为话题检测与追踪, 倾向性分析, 网络信息安全.E-mail:liupy@sdnu.edu.cn

    通讯作者:

    杨玉珍

A Topic Link Detection Method Based on Improved Information Bottleneck Theory

Funds: 

Supported by National Natural Science Foundation of China (60873247), Natural Foundation of Shandong Province (ZR2012FM038), and Science and Technology Development Plan of Shandong Province (2012GGB01194)

  • 摘要: 话题关联检测的关键任务在于判断给定报道对是否属于同一话题. 现有判断方法往往忽略种子事件与其直接相关事件之间的层次关系.为此,通过分析报道内部语义分布规律及篇章结构,并依据语义分布规则,利用语义分布规律改进信息瓶颈(Information bottleneck,IB)算法,用于子话题逻辑语义单元的划分,并利用这些逻辑语义单元表示报道,进行话题关联检测. 实验证明该方法有较快的收敛速度,并在一定程度上提高了系统性能.
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出版历程
  • 收稿日期:  2012-09-28
  • 修回日期:  2013-03-11
  • 刊出日期:  2014-03-20

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