计算机应用 ›› 2013, Vol. 33 ›› Issue (10): 2807-2810.

• 人工智能 • 上一篇    下一篇

结合时间信息的事件追踪的动态模型

徐建民1,孙晓磊1,吴树芳2,3   

  1. 1. 河北大学 数学与计算机学院,河北 保定 071002
    2. 河北软件职业技术学院 信息工程系,河北 保定 071001
    3. 河北大学 管理学院,河北 保定 071000
  • 收稿日期:2013-04-27 修回日期:2013-06-12 出版日期:2013-10-01 发布日期:2013-11-01
  • 通讯作者: 孙晓磊
  • 作者简介:徐建民(1966-),男,河北邯郸人,教授,博士,主要研究方向:信息检索、不确定信息处理;孙晓磊(1987-),女,河北石家庄人,硕士研究生,主要研究方向;信息检索、话题追踪;吴树芳(1980-),女,河北邯郸人,博士研究生,主要研究方向:信息检索、话题追踪与检测。
  • 基金资助:
    中国博士后科学基金资助项目;河北省自然科学基金资助项目

Dynamic model combining with time facter for event tracking

XU Jianmin1,SUN Xiaolei1,WU Guifang2,3   

  1. 1. College of Mathematics and Computer,Hebei University,Baoding Hebei 071002,China;
    2. Department of Information Engineering,Hebei Software Institute,Baoding Hebei 071001,China
    3. College of Management,Hebei University,Baoding Hebei 071000,China;
  • Received:2013-04-27 Revised:2013-06-12 Online:2013-11-01 Published:2013-10-01
  • Contact: SUN Xiaolei

摘要: 针对互联网新闻事件追踪,结合时间信息提出了一种用于事件追踪的动态模型。该模型将时间因素加入到传统向量模型中,在此基础上得到文档与事件包含的相同特征词之间的时间相似度,并将其应用于文档与事件的相关性计算。若文档与事件相关,则把文档中新的特征词加入事件特征词集并重新调整事件特征词集中特征词的权重和时间信息。实验采用检测错误权衡(DET)曲线进行评估,结果显示与传统向量模型相比,用于事件追踪的动态模型有效地提高了系统性能,其最小的归一化追踪损耗代价降低了约9%

关键词: 事件追踪, 动态模型, 时间因素, 事件特征词集, 追踪损耗代价

Abstract: Concerning the Internet news tracking, the study put forward a dynamic model for event tracking with reference to the time information. The dynamic model introduced the time factor into the traditional vector model to get the time similarity of the same characteristic words between the document and the event,and then applied the time similarity to calculate the similarity of the document and the event.If a document was related to the event,the new characteristic words in the document would be added to the event term set,and the weight and time information of characteristic words in the event term set should be re-adjusted. The experiment was evaluated by Detection Error Tradeoff (DET), and the results show that the dynamic model for event tracking improves the system performance effectively, and its minimum normalized cost of tracking loss is reduced by about 9%.

Key words: event tracking, dynamic model, time factor, event term set, cost of tracking loss

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