A stochastic Japanese morphological analyzer using a forward-DP backward-A* N-best search algorithm

要旨

We present a novel method for segmenting the input sentence into words and assigning parts of speech to the words. It consists of a statistical language model and an efficient two-pass N-best search algorithm. The algorithm does not require delimiters between words. Thus it is suitable for written Japanese. The proposed Japanese morphological analyzer achieved 95.1% recall and 94.6% precision for open text when it was trained and tested on the ATR Corpus.

主題