Year: 2007
Type: conference-paper
Abstract: We propose a high-performance cascaded hybrid model for Chinese NER. Firstly, we use Boosting, a standard and theoretically well-founded machine learning method to combine a set of weak classifiers together into a base system. Secondly, we introduce various types of heuristic human knowledge into Markov Logic Networks (MLNs), an effective combination of first-order logic and probabilistic graphical models to validate Boosting NER hypotheses. Experimental results show that the cascaded hybrid model significantly outperforms the state-of-the-art Boosting model.
Author: Xiaofeng Yu
Institution: Chinese University of Hong Kong
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W2003759038