Named entity recognition based on a Hidden Markov Model in part-of-speech tagging
Ryohei Ageishi, Takao Miura · 2008
In this investigation, we propose how to combine stochastis process with rule-based techniques to recognize named entity in morphological analysis. We discuss Hidden Markov Model (HMM) for tagging English texts tentatively and we focus our attention on named entity recognition. We discuss rule-based approach over n consecutive words for rule extraction and show the usefulness of our approach by some experimental results.