A Decision Tree Method for Finding and Classifying Names in Japanese Texts

This paper describes a system which uses a deci sion tree to nd and classify names in Japanese texts The decision tree uses part of speech character type and special dictionary informa tion to determine the probability that a particu lar type of name opens or closes at a given po sition in the text The output is generated from the consistent sequence of name opens and name closes with the highest probability This system does not require any human adjustment Ex periments indicate good accuracy with a small amount of training data and demonstrate the system s portability The issues of training data size and domain dependency are discussed