Research on Automatic Generation of Extraction Patterns
Jia Zheng · Zhongwen xinxi xuebao · 2004
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.