本体驱动的文本虚拟样本构造方法研究  

Research on Ontology-driven Text Virtual Sample Constructing

作　　者：王晓东[1] 郭雷[1] 方俊[1] 

机构地区：[1]西北工业大学自动化学院,西安710072

出　　处：《计算机科学》2008年第3期142-145,共4页Computer Science

基　　金：国家自然科学基金资助项目(60675015)

摘　　要：构造虚拟样本能够为机器学习中的训练集融入先验知识,从而改善标注瓶颈问题。提出了一种本体驱动的文本虚拟样本构造方法。在确保类别不变性的前提下,该方法依据领域相关本体所明晰表达的领域知识,基于本体树的点、边、子树,从同义、父子、语义同构的多个词义关系角度实现了文本虚拟样本的构造。初步实验表明,该方法与原分类及类似方法相比具有更好的分类精度和推广能力。Constructing virtual examples can incorporate prior knowledge into training set in machine learning, so as to alleviate the labeling bottleneck. An Ontology-driven scheme to construct text virtual sample is proposed. Under the precondition of label invariability, the proposal constructs virtual samples according to the domain knowledge explicitly formalized by domain-specific Ontology. Based on the different Ontology tree structures, namely nodes, edges, and sub-trees, various lexical-semantic relations, including synonymy, paternity, and semantic isomorphs, are applied into text virtual example constructing. The primary experimental results show the scheme outperforms original text catego- rizations and other similar ones in precision and generalization ability.

关 键 词：虚拟样本 文本分类 本体 本体树 领域知识 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] O157[自动化与计算机技术—计算机科学与技术]