DIRICHLET PROCESS MIXTURE MODELS FOR LEXICAL CATEGORY ACQUISITION

被引：0
|
作者：
Zhang, Bichuan [1 ]
Wang, Xiaojie [1 ]
Fang, Guannan [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Ctr Intelligence Sci & Technol, Beijing, Peoples R China
来源：
2011 IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND INTELLIGENCE SYSTEMS | 2011年
关键词：
lexical category acquisition; DPMM; evaluation metric; CHILDES;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this work, we apply Dirichlet Process Mixture Models (DPMMs) to a cognitive computational task in natural language processing (NLP): lexical category acquisition. The model takes a corpus of child-directed speech from CHILDES as input. We assess the performance using a new measure we proposed that meets three criteria: informativeness, diversity and purity. The quantitative and qualitative evaluation performed highlights the choice of the feature dimension and inherent parameters can influence the performance of DPMMs towards lexical category solutions.
引用
收藏
页码：123 / 127
页数：5
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