%0 Journal Article
%T Chinese organization names recognition with Tri-training learning<br>基于Tri-training半监督学习的中文组织机构名识别*
%A CAI Yue-hong
%A ZHU Qian
%A CHENG Xian-yia
%A <br>蔡月红
%A 朱倩
%A 程显毅a
%J 计算机应用研究
%D 2010
%I 
%X In view of the data scarcity problem in for Chinese organization names recognition, this paper presented a co-training style method for Organization Names Recognition. And proposed a novel selection method for Tri-training learning, using three classifiers: CRFs, SVMs and MBL. In Tri-training process, selected new newly labeled samples based on the selection model maximizing training utility, and computed the agreement according to the agreement scoring function. Experiments on large-scale corpus show that the proposed Tri-training learning approach can more effectively and stably exploit unlabeled data to improve the generalization ability than co-training and the standard Tri-training.
%K Chinese organization name recognition
%K semi-supervised learning
%K co-training
%K Tri-training<br>中文组织机构名
%K 半监督学习
%K 协同训练
%K Tri-training
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=DFC69F736FCAF8431660A52B32A09C82&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=CA4FD0336C81A37A&sid=23104246A5FCFCEF&eid=64963996248CBF47&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=9