Product Named Entity Recognition Based on Hierarchical Hidden Markov Model
نویسندگان
چکیده
A hierarchical hidden Markov model (HHMM) based approach of product named entity recognition (NER) from Chinese free text is presented in this paper. Characteristics and challenges in product NER is also investigated and analyzed deliberately compared with general NER. Within a unified statistical framework, the approach we proposed is able to make probabilistically reasonable decisions to a global optimization by leveraging diverse range of linguistic features and knowledge sources. Experimental results show that our approach performs quite well in two different domains.
منابع مشابه
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