Title :
Improving Chinese text Chunkings precision using Transformation-based Learning
Author :
Liu, Ying ; Liao, Panpan
Author_Institution :
Tsinghua Univ., Beijing
Abstract :
Based on text chunking using HMM, transformation-based learning is made use of to improve the precision of chunk tags further. The training data and the test data are from Penn treebank 4.0, and 13 text chunks are used. Rules are learned automatically according to the rule templates. The precision is improved 4.48%. The detailed analysis that affects the text chunking is given. Different threshold, different scale of training data, different learning equation and different rule templates can affect the precision of the text chunking.
Keywords :
hidden Markov models; learning (artificial intelligence); natural language processing; text analysis; Chinese text chunking; Penn treebank 4.0; hidden Markov model; learning equation; rule templates; transformation-based learning; Entropy; Hidden Markov models; Learning systems; Machine learning; Mathematical model; Mutual information; Support vector machine classification; Support vector machines; Testing; Training data; Text chunking; transformation-based Learning;
Conference_Titel :
Industrial Technology, 2006. ICIT 2006. IEEE International Conference on
Conference_Location :
Mumbai
Print_ISBN :
1-4244-0726-5
Electronic_ISBN :
1-4244-0726-5
DOI :
10.1109/ICIT.2006.372688
