CLUSTER-BASED AND BRUTE-CORRECTING GRAMMATICAL RULES LEARNING
作者单位：Computer Science and Engineering DepartmentShanghai Jiao Tong University
会议名称：《2003 International Conference on Natural Language Processing and Knowledge Engineering》
会议日期：2003年
学科分类：081203[工学-计算机应用技术] 08[工学] 0835[工学-软件工程] 0812[工学-计算机科学与技术（可授工学、理学学位）]
基 金：sponsored by National Natural Science Foundation of China (project number:60083003)
关 键 词：Clustering algorithm Brute-correcting progress Grammatical rules learning
摘 要：正In this paper,we propose a cluster-based and brute-correcting grammatical rules learning method which is based on some conclusions of the cognitive ***,instances of grammatical category are mapped to graphic vectors and distance between two vectors is *** set of vectors and the defined distance are proved to form a distance space. Next,this space is mapped to Euclidean space and a simple clustering algorithm is applied to acquire ***,grammatical rules are learned to describe the ***,brute-correcting progress helps to refine the *** describing the method we compare the brute-correcting progress with Eric Brill’s transformation-based learning approach[E. Brill,1995]informally and present an application in Chinese named entity recognition.