信息抽取模式自动生成方法的研究

模式匹配是信息抽取系统通常使用的方法,如何生成信息抽取模式就成为信息抽取的关键问题。由于手工编写模式的代价太大,本文尝试采用聚类方法自动生成针对中文文本的信息抽取模式。通过计算模式实例间的相似度,采用单链法聚类,将模式实例划分为不同的类别,每个类别对应一个模式,将同一类别中的模式实例进行合并就可以得到最终的信息抽取模式。以农作物信息文本为实验语料,进行了聚类测试,错分率与漏分率分别为0.21%和1.07%,合并后的模式覆盖了人工分析提出的25类中的24类。

Research on Automatic Generation of Extraction Patterns

Most information extraction (IE) systems adopt a pattern matching approach. As a result, how to generate extraction patterns has become an essential step. As the cost of man made patterns is very high, we propose a method to generate extraction patterns automatically by clustering. Calculating the similarity between pattern examples and Using single link clustering, examples of patterns can be clustered into various categories, each of which represents a pattern. We applied the method to Chinese agricultural texts. After clustering, the rate of wrong classification and rate of miss classification are 0 21% and 1 07%, respectively. The patterns obtained from merging include 24 types of the information that belong to the 25 types proposed by manual analysis.