Product Named Entity Recognition Based on Hierarchical Hidden Markov Model ∗
Liu Fei-fan, Jun Zhao, Bibo Lv, Bo Xu, Hao Yu · 2013
A hierarchical hidden Markov model (HHMM) based approach of product named entity recognition (NER) from Chinese free text is presented in this pa-per. Characteristics and challenges in product NER is also investigated and analyzed deliberately compared with general NER. Within a unified statis-tical framework, the approach we pro-posed is able to make probabilistically reasonable decisions to a global opti-mization by leveraging diverse range of linguistic features and knowledge sources. Experimental results show that our approach performs quite well in two different domains. 1