计算机工程 ›› 2012, Vol. 38 ›› Issue (10): 263-265.doi: 10.3969/j.issn.1000-3428.2012.10.081

• 开发研究与设计技术 • 上一篇    下一篇

话题案例知识库动态模型及优化策略

赵立永 1,李爱民 2   

  1. (1. 北京科技大学计算机与通信工程学院,北京 100083;2. 山东轻工业学院信息学院,济南 250353)
  • 收稿日期:2012-02-22 出版日期:2012-05-20 发布日期:2012-05-20
  • 作者简介:赵立永(1981-),男,博士研究生,主研方向:Web文本挖掘;李爱民,副教授
  • 基金项目:
    国家科技支撑计划基金资助项目(2011BAK08B04)

Dynamic Model and Optimization Strategy of Topic Case Knowledge Base

ZHAO Li-yong 1, LI Ai-min 2   

  1. (1. School of Computer & Communication Engineering, University of Science & Technology Beijing, Beijing 100083, China; 2. School of Information, Shandong Institute of Light Industry, Jinan 250353, China)
  • Received:2012-02-22 Online:2012-05-20 Published:2012-05-20

摘要: 传统的话题检测方法仅通过最初几篇话题相关报道的特征来表示话题,不能适应话题动态变化的特点。为此,提出一种话题案例知识库的动态模型。采用资源描述框架,实现话题案例知识表示,并在层次语义树基础上,利用案例融合策略实现话题案例知识库的动态更新,使用最大容忍优化策略解决话题质心漂移问题。实验结果表明,通过提高话题案例知识的全面性和内聚性,该模型能够改进话题检测和追踪的效果。

关键词: 话题检测, 案例知识库, 动态模型, 优化策略, 层次语义树, 话题质心

Abstract: As topic dynamically change over time, it is difficult to stand for all related story with feature of the first several stories. A dynamic model of topic case knowledge base is proposed in order to solve this problem. The model adopts Resource Description Framework(RDF) to represent case knowledge base, and then realizes dynamically updating of topic feature by merging case based on Hierarchical Semantic Tree(HST). In addition, it solves the problem of topic drift cased by the model with maximum enduring optimization strategy. Experimental results show that the model can greatly increase accuracy of topic detection through enhancing completeness and cohesiveness of case knowledge.

Key words: topic detection, case knowledge base, dynamic model, optimization strategy, Hierarchical Semantic Tree(HST), topic centroid

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