Fault-Tolerant Learning for Term Extraction
Yuhang Yang, Hao Yu, Yao Meng, Yingliang Lu, Yingju Xia · Institutional Repositories DataBase (IRDB) · 2010
This paper presents the Fault-Tolerant Learning approach for term extraction. The approach extract s terms using automatically generated seeds instead of prior domain knowledge or annotated corpora. Thus it is applicable to any domain specific corpus and it is especially useful for resource-limited domains. Two classifiers are separately trained for prediction and verification to ensure the performance of the proposed approach. Evaluations conducted on two different domains for Chinese term extraction show significant improvements over existing techniques and also verify the efficiency and relative domain independent nature of the approach.